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We are looking for a Tech Lead - Data Platform.
As a tech lead, you will take a leading part in designing and building the infrastructure for connecting and analyzing huge, privacy protected datasets in the cloud using Java, Spark and other technologies and mentor team members.
What You'll Do:
Design and develop platform capabilities for scalable data products tailored to enterprise customers
Collaborate with Product Managers, Software Engineers, and DevOps Engineers to gather requirements, create system and feature design documentation, and implement solutions across diverse environments
Write Java-based back-end code, leveraging Spark, various cloud services, and relational databases
Partner with the production team to define solutions, monitor services, troubleshoot issues, and identify cost optimization opportunities
Mentor and guide team engineers, providing support in their daily tasks and development
Build and use monitoring infrastructure to track services, troubleshoot problems, and optimize performance, throughput, and costs
Address privacy challenges to ensure the protection and confidentiality of consumer and patient data

We are looking for a We are looking for a.
As a Big Data Team Lead, you will lead a core team focused on the ingestion of big data and the development of core algorithms. Your role will involve building scalable and robust solutions for processing massive geospatial datasets, including spatially-focused algorithms. You will also be responsible for developing innovative big data solutions to ensure accuracy and efficiency within a fast-paced and evolving technical ecosystem. This position requires a passionate leader with a strong background in big data technologies and a drive to innovate.
RESPONSIBILITIES:
Lead and manage a big data engineering team, focused on processing high-volume spatial-temporal data, while also engaging in hands-on technical tasks.
Collaborate daily with product managers, R&D stakeholders, and data scientists to translate requirements into robust data systems.
Prioritize and scope incoming feature requests and technical improvements to balance innovation with stability.
Maintain and evolve the teams Apache Spark-based data pipelines, including optimization and scaling.
Lead technical planning sessions, foster ownership and accountability within the team.
Drive project-level KPIs and data quality KPIs such as pipeline completion time, job reliability, data freshness metrics and data accuracy.
Manage 36 direct reports.

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.

abra’s Microsoft Data Division is hiring – Data Team Lead (BI / Data Engineering) abra’s Microsoft Data Division is looking for a Data Team Lead with a strong background in BI and Data Engineering . This role combines leadership with hands-on work, managing impactful projects across diverse industries. Key Responsibilities:
* Lead and mentor a data team.
* Manage end-to-end data projects in a project-based environment.
* Collaborate with business and technical stakeholders to deliver data-driven solutions.