דרושים » דאטה » Staff Data Engineer

We are seeking a Senior Backend & Data Engineer to join its SaaS Data Platform team.
This role offers a unique opportunity to design and build large-scale, high-performance data platforms and backend services that power our cloud-based products.
You will own features end to end-from architecture and design through development and production deployment-while working closely with Data Science, Machine Learning, DevOps, and Product teams.
What Youll Do:
Design, develop, and maintain scalable, secure data platforms and backend services on AWS.
Build batch and streaming ETL/ELT pipelines using Spark, Glue, Athena, Iceberg, Lambda, and EKS.
Develop backend components and data-processing workflows in a cloud-native environment.
Optimize performance, reliability, and observability of data pipelines and backend services.
Collaborate with ML, backend, DevOps, and product teams to deliver data-powered solutions.
Drive best practices, code quality, and technical excellence within the team.
Ensure security, compliance, and auditability using AWS best practices (IAM, encryption, auditing).
Tech Stack:
AWS Services: S3, Lambda, Glue, Step Functions, Kinesis, Athena, EMR, Airflow, Iceberg, EKS, SNS/SQS, EventBridge
Languages: Python (Node.js/TypeScript a plus)
Data & Processing: batch & streaming pipelines, distributed computing, serverless architectures, big data workflows
Tooling: CI/CD, GitHub, IaC (Terraform/CDK/SAM), containerized environments, Kubernetes
Observability: CloudWatch, Splunk, Grafana, Datadog
Key Responsibilities:
Design, develop, and maintain scalable, secure backend services and data platforms on AWS
Build and operate batch and streaming ETL/ELT pipelines using Spark, Glue, Athena, Iceberg, Lambda, and EKS
Develop backend components and data processing workflows in a cloud-native environment
Optimize performance, reliability, and observability of data pipelines and backend services
Collaborate with ML, backend, DevOps, and product teams to deliver data-driven solutions
Lead best practices in code quality, architecture, and technical excellence
Ensure security, compliance, and auditability using AWS best practices (IAM, encryption, auditing)

We are seeking a seasoned and execution driven VP, head of data platform to lead all the R&D tracks of the Data and Analytics organization in our company. This role focuses on leading a complex data engineering organization at scale, driving delivery, operational excellence and cross-company enablement through world-class data platforms and tools.
This leader will serve as the engineering owner of our data platform, managing multiple data infra, data engineering and BI development teams, overseeing extensive resources, and ensuring the delivery of high-quality, scalable, and reliable data products and services. This position requires a strong technical background combined with exceptional leadership, strategic thinking, and cross-functional collaboration skills.
He will also act as a key stakeholder in defining the architecture and strategic direction of our data infrastructure, pipelines, AI/ML infra and platforms to support the company's rapid growth and evolving business needs.
Hybrid
Full-time
What youll do: 
Lead and manage the entire data platform, including:
Real-Time Data & Streaming Infrastructure: Introduce and engineer robust data streaming infrastructures (e.g., using Kafka, Pub/Sub, Dataflow) to enable near-real-time data ingestion and scalable low-latency data serving, unlocking advanced analytics and critical use cases.
Data engineering teams responsible for the data ingestion, transformation and delivery pipelines
BI infra and development teams owning the cross-company consumption layer, including BI tools, BI data layers and dashboards
Serve as the operational and delivery lead across the data platform, ensuring strong project execution, roadmap alignment and measurable business impact
Data Engineering & Architecture Oversight: Lead the design, development, and evolution of scalable data platforms, encompassing data lakes, data warehouses, and advanced data products, ensuring they meet performance, reliability, and business requirements.
Operational Excellence & Reliability: Establish and drive engineering operational excellence processes across data engineering, significantly improving data quality, availability, and system reliability. Implement frameworks for proactive monitoring, alerting, and incident management, reducing major incidents and ensuring continuous visibility into data flows.
Advanced Data Observability: Integrate and leverage cutting-edge data observability solutions (e.g., Monte Carlo) to provide comprehensive visibility into data pipelines, enabling proactive detection and resolution of anomalies.
Cross-functional Collaboration & Stakeholder Management: Collaborate extensively with product, analytics, business, and infrastructure teams to align data strategies with overarching business priorities, ensuring the delivery of high-quality data products that meet diverse user needs.
Innovation & Technology Adoption: Stay abreast of the latest data, cloud, and AI trends, driving the evaluation and adoption of modern cloud-native technologies to continuously improve platform capabilities and future-proof the ecosystem.
Leadership & Team Growth: Lead, mentor, and grow a large team of data engineers, fostering a culture of technical excellence, continuous learning, and agile methodologies. Oversee budget management and drive talent development within the team.
Data Governance & Quality: Oversee the implementation of standards for data quality, data integrity tools, governance, privacy, and regulatory compliance across the data ecosystem.

We are seeking a Data Architect to lead the design of end-to-end, enterprise data architectures that enable analytics, AI, and data-driven transformation across customer environments.
In this role, you will act as a trusted advisor, defining the architectural vision, target-state designs, and roadmaps for IBM data solutions. You will work closely with customers, sales manager, and presale engineers to translate business needs into scalable, secure, and future-ready data platforms across hybrid and multi-cloud environments.
Responsibilities:
Define data architecture vision, target-state, and roadmaps for customer environments
Design enterprise-scale architectures for data warehouses, data lakes, lakehouse, and streaming platforms
Architect data platforms to support analytics, AI, and generative AI use cases
Act as a trusted advisor to customers on data modernization, governance, and AI readiness
Ensure architectures align with security, governance, and regulatory requirements
Guide implementation teams to ensure adherence to architectural standards
Collaborate with Consulting, Sales, and Delivery teams on solution design and proposals
Contribute to IBM reference architectures, standards, and reusable patterns

Our team is responsible for the data and data infrastructure that processes billions of records daily, driving critical business insights for both internal and external customers across the organization.
Our Data team consists of highly skilled senior software and data professionals who collaborate to solve complex data challenges. We process billions of records daily from multiple sources using diverse infra and multi-stage pipelines with intricate data structures and advanced queries, and complex BI.
A bit about our infrastructure. Our main databases are Snowflake, Iceberg on AWS, and Trino. Spark on EMR processes the huge influx of data. Airflow does most of the ETL.
The data we deliver drives insights both for internal and external customers. Our internal customers use it routinely for decision-making across the organization, such enhancing our product offerings.
What Youll Do
Build, maintain, and optimize data infrastructure.
Contribute to the evolution of our AWS-based infrastructure.
Work with database technologies - Snowflake, Iceberg, Trino, Athena, and Glue.
Utilize Airflow, Spark, Kubernetes, ArgoCD and AWS.
Provide AI tools to ease data access for our customers.
Integrate external tools such as for anomaly detection or data sources ingestion.
Use AI to accelerate your development.
Assures the quality of the infra by employed QA automation methods.

Required Data Engineer
Position Overview:
We are assembling an elite, small-scale team of innovators committed to a transformative mission: advancing generative AI from conceptual breakthrough to tangible product reality. As a Senior Data Engineer, you will be the critical data backbone of our innovation engine, transforming raw data into the fuel that powers groundbreaking GenAI solutions, driving our digital intelligence capabilities to unprecedented heights.
Your Strategic Role:
You are not just a data engineer - you are a strategic enabler of GenAI innovation. Your primary mission is to:
Prepare, structure, and optimize data for cutting-edge GenAI project exploration
Design data infrastructures that support rapid GenAI prototype development
Uncover unique data insights that can spark transformative AI project ideas
Create flexible, robust data pipelines that accelerate GenAI research and development
What Sets This Role Apart:
Data as the Foundation of AI Innovation
You'll be working at the intersection of advanced data engineering and generative AI
Your data solutions will directly enable the team's ability to experiment with and develop novel AI concepts
Every data pipeline you design has the potential to unlock a breakthrough GenAI project
Exploration and Innovation
Conduct deep data exploration to identify potential GenAI application areas
Work closely with AI researchers to understand data requirements for cutting-edge GenAI projects.

we are looking for a Senior Software Engineer to join the Secrets Hub group and help evolve our modern, multi-cloud secrets management SaaS platform.
Secrets Hub integrates with AWS, Azure, GCP, and HashiCorp Vault to give organizations a centralized, secure, and seamless way to manage secrets across cloud environments. As a senior engineer, youll join a strong engineering team and contribute to the design, development, and scaling of core product services used by some of the largest enterprises in the world.
This is a hands-on role for someone passionate about solving deep technical problems, writing clean code, and working in a fast-paced, cloud-native environment.
Responsibilities:
Design, implement, and maintain secure and scalable backend services for Secrets Hub.
Collaborate with product managers, architects, and fellow engineers across multiple engineering teams.
Write clean, maintainable code in Python using AWS serverless architecture and AWS CDK.
Participate in system design discussions, architecture reviews, and code reviews.
Take part in the full development lifecycle, including planning, implementation, testing, deployment, and monitoring.
Investigate complex production issues and contribute to continuous improvement of reliability and observability.
Uphold high standards of quality, security, and performance.

Come join the team as a Senior Staff AI Engineer.
Our Data Exchange group is responsible for acquiring millions of transactions and statements a day to satisfy our customers needs in all products.
You will utilize your skills to help develop and maintain backend services leveraging AI and machine learning models, using both analytical algorithms and deep learning approaches, to acquire data from financial institutions on behalf of our users.
Responsibilities:
Lead and apply best practices in AI driven software lifecycle management, from ideation, through development and evaluation to production deployment.
Build a backend service with AI in its core at scale (millions of users and requests daily)
Collaborate with stakeholders to define success criteria and align model metrics with business goals
Work side-by-side with product managers, business analytics, data scientists, and backend engineers in enabling AI solutions for business use cases
Explore the state-of-the-art technologies and apply them to deliver customer benefits

Come join the Data Exchange group as a Software Engineer.
You will be developing high volume tools and services that are part of Data Acquisition Platform. Our Backend teams are responsible for acquiring millions of transactions and statements a day to satisfy our customers needs in all products. You will utilize your skills to help develop and maintain critical backend systems in cloud environments that are vastly used by both internal and external customers.
Responsibilities:
Identify, design and build tools that are focused on tooling work and observability work, ensuring high availability, scalability, and performance of our production systems.
Ensure the highest standards for engineering design, implementation and testing
Collaborate closely with peers, cross-functional teams and business units to define, prioritize, sequence and scope business and functional requirements and drive results forward for
Accurately scope effort, identify risks and clearly communicate trade-offs with team members and other stakeholders
Be the first level of support and handle incidents, production issues, and alerts.
Investigate production issues and provide valuable insights to the core teams.
Passionate for continuous learning, experimenting and applying cutting edge technology and software paradigms
Pursue and resolve complex or unchartered technical problems and share key learnings
Provide technical leadership and be a role model to software engineers pursuing technical career path in engineering
Stay aware of industry trends and make technology choices and strategic decisions
Mentor engineers on technology, process, people, and product skills

We are looking for a talented and experienced R&D Platform Engineer to join our dynamic team. Our organization provides cutting-edge services utilized by both internal our company services and external customers. The ideal candidate will be responsible for defining and implementing best practices that can be shared across the company and working on edge technologies on the cloud. This position encompasses all stages of the Software Development Life Cycle (SDLC), including design, development, testing, and ensuring high ROI on deliverables.
Define and implement best practices for the R&D platform.
Collaborate with internal and external stakeholders to understand requirements and deliver high-quality solutions.
Work on edge technologies and cloud platforms to enhance our services.
Participate in all phases of the SDLC, including design, development, testing, and deployment.
Ensure high ROI on deliverables by optimizing processes and solutions.
Share knowledge and best practices across the company to promote a culture of continuous improvement.

Were building foundational infrastructure to secure AI agents - including their identities, access patterns, and interactions with sensitive systems and data. This includes designing intelligent, dynamic mechanisms for ephemeral access control, secrets management, and agent/user identity tailored to modern agent frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, and beyond.
Youll help define how agents (both machine and human-facing) authenticate, receive scoped access, perform actions securely, and leave behind a verifiable audit trail.
This is a unique opportunity to be part of a start-up inside the company - building the platform from scratch at one of the most cutting-edge intersections of AI, identity, and security.
Responsibilities:
Develop secure, scalable Python services to support agent identity, secrets access, credential management, and authorization flows.
Implement JWT-based agent/user authentication, and real-time policy checks based on agent context and tool usage.
Build SDKs, wrappers, and tool integrations that enable popular agent frameworks (LangChain, LangGraph, Semantic Kernel, etc.) to securely request and use secrets.
Collaborate closely with the architect and other engineers to design components with clear boundaries and clean contracts.
Ensure secrets and credentials are injected only when needed, redacted from logs, and never persist in agent memory or prompts.
Write thorough tests and maintain high-quality, well-documented code.
Work cross-functionally with internal platform, AI, and security teams to understand requirements and refine implementation plans.