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Principal / Staff Data Platform Engineer

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Summary

A 6-month B2B contract role (100% remote from Poland) for a Principal/Staff Data Platform Engineer to lead the technical design of a new AI-first data platform — moving governed events from an Iceberg-based lakehouse into batch and near-real-time data products — using SQL, Python/Java/Scala, Spark/Flink, and AWS, while setting engineering standards and mentoring data engineers.

Start: ASAP / Flexible

Contract length: 6 months + prolongations

Contract type: B2B

Remote: 100% remote

Business trips: none

The Principal / Staff Data Platform Engineer will lead the technical development of a new AI-first data foundation, focused on transforming governed events into trusted data products and analytics.

Main Responsibilities:

  • Lead the technical design of the new data platform.

  • Define data movement from the Iceberg-based event layer to analytical and operational data products.

  • Evaluate and select technologies for data querying, transformation, orchestration, storage, and serving.

  • Design canonical entities and reusable data models across various business domains.

  • Establish scalable patterns for batch and near-real-time data processing.

  • Make architectural decisions and establish engineering standards for the platform.

  • Build data quality, observability, lineage, and reconciliation into the platform.

  • Define engineering standards for testing, deployments, versioning, and schema evolution.

  • Mentor other data engineers as the team grows.

Key Requirements:

  • Significant experience in designing and operating production data platforms.

  • Strong experience with distributed data systems and high-volume event data.

  • Deep understanding of lakehouse architectures and open table formats like Apache Iceberg.

  • Strong SQL knowledge and experience in Python, Java, or Scala.

  • Experience with distributed processing technologies like Spark or Flink.

  • Strong understanding of data modelling, performance, and storage design.

  • Experience in building both batch and near-real-time data pipelines.

  • Experience with cloud infrastructure, preferably AWS.

  • Strong understanding of CI/CD and infrastructure-as-code principles.

  • Experience with data contracts and schema evolution.

Nice to Have:

  • Experience in ad-tech or high-volume event processing.

  • Multi-tenant SaaS data architecture knowledge.

  • Experience with semantic layers.

  • Experience building data platforms for analytics and ML/AI workloads.

  • Knowledge in privacy, residency, and regulated data environments.

Skills

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See also

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