דרושים » ניהול ביניים » Application data team leader

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.

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.

We are looking for an experienced Data Engineering Team Leader.
In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data and analytics platforms.
A day in the life and how youll make an impact:
Drive the technical strategy and roadmap for the data engineering function, ensuring alignment with overall business objectives.
Own the design, development, and evolution of scalable, high-performance data pipelines to enable diverse and growing business needs.
Establish and enforce a strong data governance framework, including comprehensive data quality standards, monitoring, and security protocols, taking full accountability for data integrity and reliability.
Lead the continuous enhancement and optimization of the data analytics platform and infrastructure, focusing on performance, scalability, and cost efficiency.
Champion the complete data lifecycle, from robust infrastructure and data ingestion to detailed analysis and automated reporting, to maximize the strategic value of data and drive business growth.