Senior Data Engineer (Python)
The Role:
We are looking for a Senior Data Engineer to architect and scale the data foundations for one of our high-growth client products. The ideal candidate is a Python expert who treats data infrastructure as software, implementing CI/CD, unit testing, and observability into every layer of the modern data stack. You are a perfect candidate if you are growth-oriented, you love what you do, and you enjoy working on new ideas to develop exciting products.
What we’re looking for:
5+ years of experience building complex data processing applications using Python (Pandas, PySpark, or Dask).
Advanced SQL skills for complex transformations, window functions, and query optimization in cloud warehouses.
Deep experience with dbt (data build tool) for managing the T in ELT, including documentation and testing.
Proven experience with Apache Airflow, Prefect, or Dagster for managing complex dependency graphs.
Hands-on experience with Snowflake, BigQuery, or AWS Redshift.
Strong understanding of Dimensional Modeling (Star/Snowflake schema) and Data Vault 2.0.
Experience with Git, Docker, and implementing CI/CD for data pipelines.
Nice-to-Have:
Experience building Real-time Pipelines using Kafka or Flink.
Familiarity with Data Contracts and Data Quality frameworks (Great Expectations, Monte Carlo).
Knowledge of Vector Databases (Pinecone, Milvus) for AI/LLM applications.
Infrastructure as Code (Terraform) experience.
Responsibilities:
Build and maintain scalable, automated ELT/ETL pipelines that provide a 'single source of truth' for the organization.
Implement rigorous automated testing and monitoring to ensure data integrity and reliability.
Optimize warehouse storage and compute costs while reducing pipeline latency.
Partner with Data Scientists and Product Managers to translate business requirements into technical data models.
Promote a 'DataOps' culture within the team, conducting code reviews and sharing best practices.
What we offer:
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