Platform Engineer – Data (SDE-3 / Staff)

We are looking for a hands-on Platform Engineer – Data to take ownership of a large-scale, billion-row shared data platform and help scale it from its current state to the next level of reliability, performance, and usability.

This is a data platform engineering role, not a business ETL or analytics-pipeline delivery position. You will design, build, and operate the foundational systems that product and engineering teams rely on. The role requires strong distributed-systems expertise, production engineering skills, and the ability to drive architecture while remaining deeply involved in coding and operations.

Requirements

What You’ll Own

• Build and evolve open-lakehouse foundations using technologies such as Apache Iceberg, Delta Lake, or Apache Hudi, including table lifecycle management, partitioning, data layout, compaction, schema evolution, catalog management, and query operations.
• Design and operate batch and streaming ingestion systems, including CDC, data contracts, deduplication, checkpointing, replay, recovery, and failure handling.
• Develop platform services, APIs, and self-service capabilities that enable engineering and product teams to consume and manage data independently without creating unnecessary dependencies on a central platform team.
• Build and manage orchestration and workload execution systems across Kubernetes and workflow technologies such as Prefect, Argo, or Airflow.
• Establish robust metadata, lineage, governance, data quality, and observability capabilities across the platform.
• Own production reliability and operational excellence, including incident response, SLAs, data freshness, performance and cost optimization, capacity planning, and recovery improvements.
• Establish engineering standards and architectural patterns that enable the platform to scale across teams and workloads.

What We’re Looking For

• Typically 7+ years of software or platform engineering experience, with demonstrated SDE-3 / Staff-level ownership and impact, regardless of current job title.
• Proven, hands-on experience owning a shared data platform in production, rather than exclusively building pipelines or applications on top of an existing platform.
• Strong expertise in distributed-systems design and production-grade software development using one or more of Python, Java, Go, or Scala.
• Meaningful experience across batch processing, streaming, data ingestion/CDC, storage and query systems, and platform operations.
• Demonstrated ability to improve reliability, scalability, performance, cost efficiency, or developer self-service in large-scale production environments.
• Strong individual contributor who can influence architecture, establish technical standards, and drive complex engineering initiatives while remaining close to the code and operational details.
• Comfortable taking end-to-end ownership, from architecture and implementation through deployment, monitoring, incident response, and continuous improvement.

Strong Adjacent Experience

Experience with open-source or production-scale implementations involving:

• Apache Iceberg, Apache Hudi, or Delta Lake
• Apache Kafka, Apache Flink, or Debezium
• Apache Spark, Trino, or Pinot
• Kubernetes and cloud-native workload platforms
• Data catalogs, metadata platforms, lineage systems, or governance frameworks
• Data quality and observability platforms

Not a Fit For This Role

This role is not intended for candidates whose experience is primarily focused on:

• BI or reporting
• Analytics engineering
• Data warehouse modeling
• Business-facing ETL development only
• Generic backend engineering without significant data-platform ownership
• Assembly and configuration of managed services without deep platform engineering ownership
• Narrow ownership of a single infrastructure or data component
• People-management-focused roles without substantial hands-on engineering involvement

Must-Have Skills

• Data Platform
• Distributed Systems

Good-to-Have Skills

• Apache Iceberg
• Apache Hudi
• Delta Lake