דרושים » דאטה » Senior Data Engineer

We are looking for a Staff Data Engineer to join our Platform group as part of the Data Infrastructure team. This is a senior individual contributor role for someone who combines deep technical expertise with a passion for building scalable, high-impact data infrastructure.
In this role, you will take ownership of designing, implementing, and evolving the data systems that power data orchestration, distributed storage, and streaming capabilities - with a focus on architecture, reliability, and performance. Youll collaborate across teams, influence engineering best practices, and help scale our infrastructure to support growing data needs across the organization.

Were looking for a Senior Backend Engineer - Data Infrastructure to design and optimize high-performance infrastructure capable of handling massive data volumes. In this role, youll lead backend development, architect scalable data pipelines, and ensure seamless data processing. Your expertise in distributed systems and performance optimization will drive innovation, transforming intricate security challenges into efficient, resilient solutions.

Responsibilities
Be a significant part of the development of backend infrastructure to efficiently handle, process, and store vast volumes of data.
Architect and build a scalable, high-performance backend system that supports various services within the platform.
Translate intricate requirements into meticulous backend design plans, maintaining a focus on software design, code quality, and performance.
Collaborate with cross-functional teams to implement backend and data-handling techniques.
Apply your expertise to create robust backend solutions.
Leverage your proficiency in cloud platforms such as AWS, GCP, or Azure to drive strong backend engineering practices.
Demonstrate strong debugging skills, identifying issues such as race conditions and memory leaks within the backend system. Solve complex backend problems with an analytical mindset and contribute to a positive team dynamic.
Bring your excellent interpersonal skills to foster collaboration and maintain a positive attitude within the team.

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructuresomeone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacksits about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakesdesigned for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.

we are looking for a Senior Data Engineer
What You'll Do:

Shape the Future of Data - Join our mission to build the foundational pipelines and tools that power measurement, insights, and decision-making across our product, analytics, and leadership teams.
Develop the Platform Infrastructure - Build the core infrastructure that powers our data ecosystem including the Kafka events-system, DDL management with Terraform, internal data APIs on top of Databricks, and custom admin tools (e.g. Django-based interfaces).
Build Real-time Analytical Applications - Develop internal web applications to provide real-time visibility into platform behavior, operational metrics, and business KPIs integrating data engineering with user-facing insights.
Solve Meaningful Problems with the Right Tools - Tackle complex data challenges using modern technologies such as Spark, Kafka, Databricks, AWS, Airflow, and Python. Think creatively to make the hard things simple.
Own It End-to-End - Design, build, and scale our high-quality data platform by developing reliable and efficient data pipelines. Take ownership from concept to production and long-term maintenance.
Collaborate Cross-Functionally - Partner closely with backend engineers, data analysts, and data scientists to drive initiatives from both a platform and business perspective. Help translate ideas into robust data solutions.
Optimize for Analytics and Action - Design and deliver datasets in the right shape, location, and format to maximize usability and impact - whether thats through lakehouse tables, real-time streams, or analytics-optimized storage.
You will report to the Data Engineering Team Lead and help shape a culture of technical excellence, ownership, and impact.

We are growing and are looking for a Senior Data Platform Engineer
who value personal and career growth, team-work, and winning!
What your day will look like:
Design, plan, and build all aspects of the platforms data, machine learning (ML) pipelines, and infrastructure.
Build and optimize an AWS-based Data Lake using best practices in cloud architecture, data partitioning, metadata management, and security to support enterprise-scale data operations.
Collaborate with engineers, data analysts, data scientists, and other stakeholders to understand data needs.
Solve challenging data integration problems, utilizing optimal ETL/ELT patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
Lead end-to-end data projects from infrastructure design to production monitoring.

We are growing and are looking for a Senior Data Infra Engineer
who value personal and career growth, team-work, and winning!
What your day will look like:
Design, plan, and build all aspects of the platforms data, machine learning (ML) pipelines, and infrastructure.
Build and optimize an AWS-based Data Lake using best practices in cloud architecture, data partitioning, metadata management, and security to support enterprise-scale data operations.
Collaborate with engineers, data analysts, data scientists, and other stakeholders to understand data needs.
Solve challenging data integration problems, utilizing optimal ETL/ELT patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
Lead end-to-end data projects from infrastructure design to production monitoring.

We are looking for a Senior Data Engineer.
As a Senior Data Engineer, youll be more than just a coder - youll be the architect of our data ecosystem. Were looking for someone who can design scalable, future-proof data pipelines and connect the dots between DevOps, backend engineers, data scientists, and analysts.
Youll lead the design, build, and optimization of our data infrastructure, from real-time ingestion to supporting machine learning operations. Every choice you make will be data-driven and cost-conscious, ensuring efficiency and impact across the company.
Beyond engineering, youll be a strategic partner and problem-solver, sometimes diving into advanced analysis or data science tasks. Your work will directly shape how we deliver innovative solutions and support our growth at scale.
Responsibilities:
Design and Build Data Pipelines: Architect, build, and maintain our end-to-end data pipeline infrastructure to ensure it is scalable, reliable, and efficient.
Optimize Data Infrastructure: Manage and improve the performance and cost-effectiveness of our data systems, with a specific focus on optimizing pipelines and usage within our Snowflake data warehouse. This includes implementing FinOps best practices to monitor, analyze, and control our data-related cloud costs.
Enable Machine Learning Operations (MLOps): Develop the foundational infrastructure to streamline the deployment, management, and monitoring of our machine learning models.
Support Data Quality: Optimize ETL processes to handle large volumes of data while ensuring data quality and integrity across all our data sources.
Collaborate and Support: Work closely with data analysts and data scientists to support complex analysis, build robust data models, and contribute to the development of data governance policies.

We are looking for an experienced Backend Developer to join the OptiPromo team. You will be responsible for designing, building, and maintaining scalable backend services that empower our Promotions capabilities. Youll work in a modern, cloud-native environment with a strong focus on performance, scale, reliability, and clean software design.
Responsibilities:
Design and implement backend services using Java and Node.js, following OOP principles
Design and build batch and streaming data pipelines using Apache Beam
Develop scalable, secure, and observable services using GCP tools such as BigTable, Dataflow, and BigQuery
Define and use Protobuf-based DTOs to support structured data exchange across services
Collaborate closely with product and architecture teams to extend the promotion engine and related systems
Write clean, testable, and efficient code based on SOLID principles
Participate in code reviews, design sessions, and contribute to technical documentation.

We are looking for a hands-on Data Specialist to join our growing data group, working on the practical backbone of high-scale, financial-grade systems. Youll work closely with engineers, BI, product, and business stakeholders, expert in design, build, and optimize data pipelines and integrations in a cloud-native environment.
If you thrive on solving complex data challenges, enjoy getting deep into code, and want to make an impact on fintech infrastructure, wed love to meet you.
Your Day-to-Day:
Develop, maintain, and optimize robust data pipelines and integrations across multiple systems
Build and refine data models to support analytics and operational needs
Work hands-on with data orchestration, transformation, and cloud infrastructure (AWS/Azure)
Collaborate with engineering, BI, and business teams to translate requirements into scalable data solutions
Contribute to data governance, data quality, and monitoring initiatives
Support implementation of best practices in data management and observability

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.