#### **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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