What You'll Do:

📍Design, build, and scale performant data pipelines and infrastructure, primarily using ClickHouse, Python, and dbt. 📍Build systems that handle large-scale streaming and batch data, with a strong emphasis on correctness and operational stability. 📍Own the end-to-end lifecycle of data pipelines, from raw ingestion to clean, well-defined datasets consumed by downstream teams. 📍Improve pipeline observability, data quality checks, and failure handling to ensure predictable operation at scale. 📍Collaborate closely with data consumers (data engineers, product engineers, researchers) to define clear dataset contracts and schemas. 📍Use AI tools and agents such as Cursor, MCPs, and LLMs to accelerate development, automate repetitive work, and boost quality. 📍Bring fresh thinking to the table, staying current with best practices and evolving your toolkit over time.

What We're Looking For:

📍Proven experience building and operating production data pipelines that run continuously and reliably. 📍Strong data engineering and software engineering fundamentals, with deep experience in Python and SQL. 📍Hands-on experience with ClickHouse and dbt in production environments. 📍Solid understanding of streaming and batch ingestion patterns, including backfills, reprocessing, and schema evolution. 📍Comfortable working across the data infrastructure stack: ingestion, transformation, storage, and exposure to downstream systems.

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