דרושים » ניהול ביניים » מנהל /ת פלטפורמת Jira ומדדים ארגוניים (KPIs) חטיבה טכנולוגית

Were looking for a hands-on leader to take ownership of our data and analytics landsape.
This isnt a pure management role we need someone who can roll up their sleeves, dive into AWS environments, and still have the strategic view to guide a growing data team.
The ideal candidate combines strong technical expertise in data engineering and analytics with a solid understanding and genuine passion for Artificial Intelligence (AI) including how AI can enhance data-driven decision-making and operational efficiency in the financial domain.
In this position youll:
Shape the companys overall data strategy and decide how we store, move, and use data across the business.
Lead a small but growing group of engineers, analysts, and BI specialists, making sure they have the right tools and direction.
Stay close to the technology designing and reviewing data pipelines, checking performance, and being the go-to person for AWS data solutions like Redshift, Glue, Athena, S3, and others.
Work with business leaders (finance, risk, compliance) to turn their questions into clear, data-driven answers.
Identify opportunities to integrate AI/ML into data workflows and business processes.
Establish best practices for data governance, quality, and security in a financial services org.
Drive automation and efficiency through modern data and AI tools

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.