Posted:1 week ago|
Platform:
Work from Office
Full Time
Design, build, and maintain data quality systems and pipelines. Work with tools such as Snowflake, Docker/Kubernetes, and Kafka to enable scalable, observable data movement. Collaborate cross-functionally to close skill gaps in DQ and data platform tooling. Contribute to building internal tooling that supports schema validation, data experimentation, and automated checks. Collaborate cross-functionally with data producers, analytics engineers, platform teams, and business stakeholders. Own the reliability, scalability, and performance of ingestion systems deployed on AWS Architect and build core components of our real-time ingestion platform using Kafka, Snowpipe Streaming. Champion software engineering excellence including testing, observability, CI/CD, and automation Drive the development of platform tools that ensure data quality, observability, and lineage through Protobuf-based schema management.. Participate in the implementation of ingestion best practices and reusable frameworks across data and software engineering teams. Core Skills: Solid programming experience (preferably in Java ) Experience with distributed data systems ( Kafka, Snowflake ) Familiarity with Data Quality tooling and concepts Good working knowledge of SQL (especially for diagnostics and DQ workflows) Experience with containerization (Docker, Kubernetes ) Strong debugging, observability, and pipeline reliability practices What You Bring: A systems mindset with strong software engineering fundamentals. Passion for building resilient, high-throughput, real-time platforms. Ability to influence technical direction across teams and drive alignment. Strong communication and mentoring skills. A bias toward automation, continuous improvement, and platform thinking. Nice to Haves: Experience with GenAI tools or supporting ML/AI data workflows Familiarity with cloud-native data platforms (e.g., AWS, GCP) Exposure to dbt or ELT frameworks
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