Senior Data Platform Engineer - Applied AI Engineering Group

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8504233

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11/12/2025

Data Platform Engineering Lead

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for a hands-on data infrastructure and platform engineer with proven leadership skills to lead and evolve our self-service data platform that powers petabyte-scale batch and streaming, near-real-time analytics, experimentation, and the feature platform. Youll guide an already excellent team of senior engineers, own reliability and cost efficiency, and be the focal point for pivotal, company-wide data initiatives- feature platform, lakehouse, and streaming.
Own the lakehouse backbone: Mature Iceberg at high scalepartitioning, compaction, retention, metadataand extend our IcebergManager in-house product to automate the lakehouse management in a self serve fashion.
Unify online/offline for features: Drive Flink adoption and patterns that keep features consistent and low-latency for experimentation and production.
Make self-serve real: Build golden paths, templates, and guardrails so product/analytics/DS engineers can move fast safely.
Run multi-tenant compute efficiently: EMR on EKS powered by Karpenter on Spot instances; right-size Trino/Spark/Druid for performance and cost.
Cross-cloud interoperability: BigQuery + BigLake/Iceberg interop where it makes sense (analytics, experimentation, partnership).
What you'll be doing
Leading a senior Data Platform team: setting clear objectives, unblocking execution, and raising the engineering bar.
Owning SLOs, on-call, incident response, and postmortems for core data services.
Designing and operating EMR on EKS capacity profiles, autoscaling policies, and multi-tenant isolation.
Tuning Trino (memory/spill, CBO, catalogs), Spark/Structured Streaming jobs, and Druid ingestion/compaction for sub-second analytics.
Extending Flink patterns for the feature platform (state backends, checkpointing, watermarks, backfills).
Driving FinOps work: CUR-based attribution, S3 Inventory-driven retention/compaction, Reservations/Savings Plans strategy, OpenCost visibility.
Partnering with product engineering, analytics, and data science & ML engineers on roadmap, schema evolution, and data product SLAs.
Leveling up observability (Prometheus/VictoriaMetrics/Grafana), data quality checks, and platform self-service tooling.

Requirements:
2+ years leading engineers (team lead or manager) building/operating large-scale data platforms; 5+ years total in Data Infrastructure/DataOps roles.
Proven ownership of cloud-native data platforms on AWS: S3, EMR (preferably EMR on EKS), IAM, Glue/Data Catalog, Athena.
Production experience with Apache Iceberg (schema evolution, compaction, retention, metadata ops) and columnar formats (Parquet/Avro).
Hands-on depth in at least two of: Trino/Presto, Apache Spark/Structured Streaming, Apache Druid, Apache Flink.
Strong conceptual understanding of Kubernetes (EKS), including autoscaling, isolation, quotas, and observability
Strong SQL skills and extensive experience with performance tuning, with solid proficiency in Python/Java.
Solid understanding of Kafka concepts, hands-on experience is a plus
Experience running on-call for data platforms and driving measurable SLO-based improvements.
You might also have
Experience building feature platforms (feature definitions, materialization, serving, and online/offline consistency).
Airflow (or similar) at scale; Argo experience is a plus.
Familiarity with BigQuery (and ideally BigLake/Iceberg interop) and operational DBs like Aurora MySQL.
Experience with Clickhouse / Snowflake / Databricks / Starrocks.
FinOps background (cost attribution/showback, Spot strategies).
Data quality, lineage, and cataloging practices in large orgs.
IaC (Terraform/CloudFormation).

This position is open to all candidates.

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8454253

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23/12/2025

Senior Data Platform Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for a Senior Data Platform Engineer to design, build, and scale next-generation data platform, the backbone powering our AI-driven insights.
This role sits at the intersection of data engineering, infrastructure, and MLOps, owning the architecture and reliability of our data ecosystem end-to-end.
Youll work closely with data scientists,r&d teams, analysts to create a robust platform that supports varying use cases, complex ingestion, and AI-powered analytics.
Responsibilities:
Architect and evolve a scalable, cloud-native data platform that supports batch, streaming, analytics, and AI/LLM workloads across R&D.
Help define and implement standards for how data is modeled, stored, governed, and accessed
Design and build data lakes and data warehouses
Develop and maintain complex, reliable, and observable data pipelines
Implement data quality, validation, and monitoring frameworks
Collaborate with ML and data science teams to connect AI/LLM workloads to production data pipelines, enabling RAG, embeddings, and feature engineering flows.
Manage and optimize relational and non-relational datastores (Postgres, Elasticsearch, vector DBs, graph DBs).
Build internal tools and self-service capabilities that enable teams to easily ingest, transform, and consume data.
Contribute to data observability, governance, documentation, and platform visibility
Drive strong engineering practices
Evaluate and integrate emerging technologies that enhance scalability, reliability, and AI integration in the platform.

Requirements:
7+ years experience building/operating data platforms
Strong Python programming skills
Proven experience with cloud data lakes and warehouses (Databricks, Snowflake, or equivalent).
Data orchestration experience (Airflow)
Solid understanding of AWS services
Proficiency with relational databases and search/analytics stores
Experience designing complex data pipelines, managing data quality, lineage, and observability in production.
Familiarity with CI/CD, GitOps, and IaC
Excellent understanding of distributed systems, data partitioning, and schema evolution.
Strong communication skills, ability to document and present technical designs clearly.
Advantages:
Experience with vector databases and graph databases
Experience integrating AI/LLM workloads into data pipelines (feature stores, retrieval pipelines, embeddings).
Familiarity with event streaming and CDC patterns.
Experience with data catalog, lineage, or governance tools
Knowledge of monitoring and alerting stacks
Hands-on experience with multi-source data product architectures.

This position is open to all candidates.

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8470086

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לפני 12 שעות

Data Engineering Team Lead - Applied AI Engineering Group

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

It starts with you - a technical leader whos passionate about data pipelines, data modeling, and growing high-performing teams. You care about data quality, business logic correctness, and delivering trusted data products to analysts, data scientists, and AI systems. Youll lead the Data Engineering team in building ETL/ELT pipelines, dimensional models, and quality frameworks that turn raw data into actionable intelligence.
If you want to lead a team that delivers the data products powering mission-critical AI systems, join mission - this role is for you.
:Responsibilities
Lead and grow the Data Engineering team - hiring, mentoring, and developing engineers while fostering a culture of ownership and data quality.
Define the data modeling strategy - dimensional models, data marts, and semantic layers that serve analytics, reporting, and ML use cases.
Own ETL/ELT pipeline development using platform tooling - orchestrated workflows that extract from sources, apply business logic, and load into analytical stores.
Drive data quality as a first-class concern - validation frameworks, testing, anomaly detection, and SLAs for data freshness and accuracy.
Establish lineage and documentation practices - ensuring consumers understand data origins, transformations, and trustworthiness.
Partner with stakeholders to understand data requirements and translate them into well-designed data products.
Build and maintain data contracts with consumers - clear interfaces, versioning, and change management.
Collaborate with Data Platform to define requirements for new platform capabilities; work with Datastores on database needs; partner with ML, Data Science, Analytics, Engineering, and Product teams to deliver trusted data.
Design retrieval-friendly data products - RAG-ready paths, feature tables, and embedding pipelines - while maintaining freshness and governance SLAs.

Requirements:
8+ years in data engineering, analytics engineering, or BI development, with 2+ years leading teams or technical functions. Hands-on experience building data pipelines and models at scale.
Data modeling - Dimensional modeling (Kimball), data vault, or similar; fact/dimension design, slowly changing dimensions, semantic layers
Transformation frameworks - dbt, Spark SQL, or similar; modular SQL, testing, documentation-as-code
Orchestration - Airflow, Dagster, or similar; DAG design, dependency management, scheduling, failure handling, backfills
Data quality - Great Expectations, dbt tests, Soda, or similar; validation rules, anomaly detection, freshness monitoring
Batch processing - Spark, SQL engines; large-scale transformations, optimization, partitioning strategies
Lineage & cataloging - DataHub, OpenMetadata, Atlan, or similar; metadata management, impact analysis, documentation
Messaging & CDC - Kafka, Debezium; event-driven ingestion, change data capture patterns
Languages - SQL (advanced), Python; testing practices, code quality, version control

This position is open to all candidates.

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8504281

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31/12/2025

Data Architect

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

As a Data Architect, youll sit at the intersection of data engineering, ML systems, and platform architecture. Youll own the patterns, guardrails, and data platform capabilities that let teams ship AI-native, low-latency experiences at scale-safely, reliably, and cost-effectively.

What Youll Actually Do:

Design AI-native data systems: LLM/RAG pipelines, embeddings & vector search, and real-time inference- production-grade and observable.
Evolve the data platform: Batch + streaming + lakehouse; CDC, orchestration, lineage/quality, and clear data contracts for ML readiness.
Set org standards: Contract-first APIs & event schemas, ADRs, SLOs (latency/MTTR/cost); lead design reviews and architecture spikes.
Modernize pragmatically: Guide adoption of Databricks, Kafka, Airflow, Kubernetes, Terraform, and modern observability- fit to purpose.
Lead by influence: Mentor Tech Leads, partner with Product/ML/Platform, and turn goals into resilient, measurable systems.

Requirements:
5+ years as a Software/Data/Solution Architect in AI-intensive or data-heavy environments; ~10+ years engineering overall.
Distributed systems depth: microservices, event-driven design, backpressure/idempotency, retries/DLQs; contract-first APIs.
Data platform expertise: streaming + batch + lakehouse, CDC, orchestration, governance/lineage, schema evolution.
AI systems fluency: LLMs, embeddings, vector stores, RAG; real-time production inference.
Hands-on: Python or TypeScript/Scala; Databricks, Airflow, Kafka, Kubernetes, Terraform; Prometheus/Grafana/Coralogix.
Cloud-first (AWS preferred), security-by-design, crisp writing and collaboration.

This position is open to all candidates.

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8481848

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01/01/2026

Staff Data Engineer, Group Tech Lead

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Were looking for an experienced and passionate Staff Data Engineer to join our Data Platform group in TLV as a Tech Lead. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of our companys data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives our company toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
In this role youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams
Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights
Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance
Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights
Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions
Collaborate closely with other Staff Engineers across our company to align on cross-organizational initiatives and technical strategies
Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions
Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization.

Requirements:
8+ years of experience in data-related roles such as Data Engineer, Data Infrastructure Engineer, BI Engineer, or Machine Learning Platform Engineer, with significant experience in at least two of these areas
A B.Sc. in Computer Science or a related technical field (or equivalent experience)
Extensive expertise in designing and implementing Data Lakes and Data Warehouses, including strong skills in data modeling and building scalable storage solutions
Proven experience in building large-scale data infrastructures, including both batch processing and streaming pipelines
A deep understanding of Machine Learning infrastructure, including tools and frameworks that enable Data Scientists to efficiently develop, deploy, and maintain models in production, an advantage
Proficiency in Python, Pulumi/Terraform, Apache Spark, AWS, Kubernetes (K8s), and Kafka for building scalable, reliable, and high-performing data solutions
Strong knowledge of databases, including SQL (schema design, query optimization) and NoSQL, with a solid understanding of their use cases
Ability to work in an office environment a minimum of 3 days a week
Enthusiasm about learning and adapting to the exciting world of AI - a commitment to exploring this field is a fundamental part of our culture.

This position is open to all candidates.

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8482879

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2 ימים

Senior DevOps Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

we are looking for a Senior DevOps Engineer with a strong software development background to build and evolve our internal DevOps platform. You will sit at the intersection of Platform Engineering, SRE, and MLOps - owning the infrastructure and tooling that powers production and enables our developers and data teams to move fast, safely, and with confidence.
If you believe DevOps should be a self-service platform, love automation, and naturally think in systems and end-to-end flows, keep reading.
What You Will Do:
Build a DevOps Platform (Platform-as-a-Product): Create internal services and golden paths that scale across teams (self-service over ad-hoc, repeatable over personal support).
Own CI/CD End-to-End: Design, build, and maintain Jenkins and GitHub Actions pipelines that move code from commit to production with high reliability, visibility, and safety.
Operate and Evolve Our AWS Stack: Hands-on ownership of AWS, including services such as ECS, EKS, Lambda, WorkSpaces, DynamoDB, Redshift, S3, DocumentDB (and the surrounding networking, IAM, observability, and deployment patterns).
Enable MLOps and Data Workflows: Support and automate ML and data pipelines using tools like Airflow, MLflow, and Jupyter Notebooks (plus integrations with compute, storage, and security controls).
Automation First: Eliminate manual work through Infrastructure-as-Code, scripting, and internal tooling. Build reusable components instead of one-off solutions.
Cost Optimization (FinOps): Drive cost visibility and optimization (tagging, budgets/alerts, rightsizing, workload efficiency, and practical trade-offs between cost and reliability).
Security Ownership: Bake security into pipelines and infrastructure (least privilege, secrets management, supply chain controls, vulnerability scanning, hardening, and incident readiness).
Leverage AI to Move Faster: Use AI tools such as Cursor, GitHub Copilot, and Claude Code to accelerate delivery (without compromising quality, security, or reliability).
Cross-Team Collaboration: Partner with Engineering, Data, and AI teams to unblock delivery, improve developer experience, and keep production stable.

Requirements:
5+ years hands-on experience in DevOps / SRE / Platform Engineering, ideally in a SaaS production environment.
Strong development background: You write code comfortably (not just scripts), build internal tools, and approach infra work with software engineering discipline (design, readability, testing, code review).
Proven experience with AWS, including ECS, EKS, Lambda, WorkSpaces, DynamoDB, Redshift, S3, DocumentDB.
Strong CI/CD experience with Jenkins, GitHub, and GitHub Actions (secure, reusable pipelines and good workflow hygiene).
Experience with ML/data tooling such as Airflow, MLflow, and Jupyter Notebooks.
Hands-on with AI-assisted development tools (Cursor, GitHub Copilot, Claude Code) and a pragmatic approach to using them effectively.
Demonstrated cost optimization experience (FinOps mindset, measurement, and continuous improvement).
Demonstrated security experience (cloud security fundamentals, IAM, secrets, secure SDLC, and operational security).
A wide-angle thinker: you naturally see the whole system, understand dependencies, and build solutions that scale across teams.
Strong communication and collaboration skills.

This position is open to all candidates.

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8499611

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17/12/2025

Senior Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from an HPE office.
Job Description:
We are looking for a highly skilled Senior Data Engineer with strong architectural expertise to design and evolve our next-generation data platform. You will define the technical vision, build scalable and reliable data systems, and guide the long-term architecture that powers analytics, operational decision-making, and data-driven products across the organization.
This role is both strategic and hands-on. You will evaluate modern data technologies, define engineering best practices, and lead the implementation of robust, high-performance data solutionsincluding the design, build, and lifecycle management of data pipelines that support batch, streaming, and near-real-time workloads.
What Youll Do
Architecture & Strategy
Own the architecture of our data platform, ensuring scalability, performance, reliability, and security.
Define standards and best practices for data modeling, transformation, orchestration, governance, and lifecycle management.
Evaluate and integrate modern data technologies and frameworks that align with our long-term platform strategy.
Collaborate with engineering and product leadership to shape the technical roadmap.
Engineering & Delivery
Design, build, and manage scalable, resilient data pipelines for batch, streaming, and event-driven workloads.
Develop clean, high-quality data models and schemas to support analytics, BI, operational systems, and ML workflows.
Implement data quality, lineage, observability, and automated testing frameworks.
Build ingestion patterns for APIs, event streams, files, and third-party data sources.
Optimize compute, storage, and transformation layers for performance and cost efficiency.
Leadership & Collaboration
Serve as a senior technical leader and mentor within the data engineering team.
Lead architecture reviews, design discussions, and cross-team engineering initiatives.
Work closely with analysts, data scientists, software engineers, and product owners to define and deliver data solutions.
Communicate architectural decisions and trade-offs to technical and non-technical stakeholders.

Requirements:
610+ years of experience in Data Engineering, with demonstrated architectural ownership.
Expert-level experience with Snowflake (mandatory), including performance optimization, data modeling, security, and ecosystem components.
Expert proficiency in SQL and strong Python skills for pipeline development and automation.
Experience with modern orchestration tools (Airflow, Dagster, Prefect, or equivalent).
Strong understanding of ELT/ETL patterns, distributed processing, and data lifecycle management.
Familiarity with streaming/event technologies (Kafka, Kinesis, Pub/Sub, etc.).
Experience implementing data quality, observability, and lineage solutions.
Solid understanding of cloud infrastructure (AWS, GCP, or Azure).
Strong background in DataOps practices: CI/CD, testing, version control, automation.
Proven leadership in driving architectural direction and mentoring engineering teams
Nice to Have
Experience with data governance or metadata management tools.
Hands-on experience with DBT, including modeling, testing, documentation, and advanced features.
Exposure to machine learning pipelines, feature stores, or MLOps.
Experience with Terraform, CloudFormation, or other IaC tools.
Background designing systems for high scale, security, or regulated environments.

This position is open to all candidates.

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8461496

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08/12/2025

Data Engineering Lead

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking a Data Engineering Lead to own and scale data platform infrastructure

Build our new data Lakehouse to support various product and business needs
Support cutting-edge AI Agents and cybersecurity use cases
Be part of the Data and AI Algorithms group
Collaborate closely with dev teams, AI/ML engineers, security researchers and business teams
Ensure the availability, reliability and quality of our data infrastructure
Help define best practices for data modeling and orchestration at scale

Requirements:
6+ years of hands-on experience in building, modelling and managing data warehouse at scale - Must
Production experience with big-data distributed systems such as Apache Spark, Ray or similar - Must
Hands-on with modern data lakes and open table formats (Delta Lake, Apache Iceberg) - Must
Experience in batch and streaming processing pipelines - Must
Strong coding skills in Python. Strong CI/CD and infrastructure-as-code capabilities.
Experience with cloud-native data services (e.g., AWS EMR, Athena, Azure Data Explorer etc.).
Familiarity with orchestration tools like Airflow, Kubeflow, Dagster or similar
Excellent communication skills, ownership mindset, and problem-solving capabilities

This position is open to all candidates.

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8448818

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3 ימים

Senior Data Engineer I - GenAI Foundation Models

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Required Senior Data Engineer I - GenAI Foundation Models
21679
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

דרישות:
Bachelors or masters degree in computer science, Engineering, Statistics, or a related field.
Minimum of 6 years of experience as a Data Engineer or a similar role, with a consistent record of successfully delivering ML/Data solutions.
You have built production data pipelines in the cloud, setting up data-lake and server-less solutions; ‌ you have hands-on experience with schema design and data modeling and working with ML scientists and ML engineers to provide production level ML solutions.
You have experience designing systems E2E and knowledge of basic concepts (lb, db, caching, NoSQL, etc)
Strong programming skills in languages such as Python and Java.
Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.
Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.
Experience with Data Warehousing and ETL/ELT pipelines
Experience in data processing for large-scale language models like GPT, BERT, or similar architectures - an advantage.
Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and המשרה מיועדת לנשים ולגברים כאחד.

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8498339

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29/12/2025

Senior Data Infra Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

we are seeking a Senior Data Infra Engineer. You will be responsible for designing and building all data, ML pipelines, data tools, and cloud infrastructure required to transform massive, fragmented data into a format that supports processes and standards. Your work directly empowers business stakeholders to gain comprehensive visibility, automate key processes, and drive strategic impact across the company.
Responsibilities
Design and Build Data Infrastructure: Design, plan, and build all aspects of the platform's data, ML pipelines, and supporting infrastructure.
Optimize Cloud Data Lake: Build and optimize an AWS-based Data Lake using cloud architecture best practices for partitioning, metadata management, and security to support enterprise-scale operations.
Lead Project Delivery: Lead end-to-end data projects from initial infrastructure design through to production monitoring and optimization.
Solve Integration Challenges: Implement optimal ETL/ELT patterns and query techniques to solve challenging data integration problems sourced from structured and unstructured data.

Requirements:
Experience: 5+ years of hands-on experience designing and maintaining big data pipelines in on-premises or hybrid cloud SaaS environments.
Programming & Databases: Proficiency in one or more programming languages (Python, Scala, Java, or Go) and expertise in both SQL and NoSQL databases.
Engineering Practice: Proven experience with software engineering best practices, including testing, code reviews, design documentation, and CI/CD.
AWS Experience: Experience developing data pipelines and maintaining data lakes, specifically on AWS.
Streaming & Orchestration: Familiarity with Kafka and workflow orchestration tools like Airflow.
Preferred Qualifications
Containerization & DevOps: Familiarity with Docker, Kubernetes (K8S), and Terraform.
Modern Data Stack: Familiarity with the following tools is an advantage: Kafka, Databricks, Airflow, Snowflake, MongoDB, Open Table Format (Iceberg/ Delta)
ML/AI Infrastructure: Experience building and designing ML/AI-driven production infrastructures and pipelines.

This position is open to all candidates.

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8478237

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