Senior Data Engineer

Contract Details: Contract, 6 months, with renewal.

Main Tech Stack: Python / Airflow, SQL / dbt, Snowflake, PostgreSQL, Kafka

Scope of Work:

• Data platform focused. No end-user UI. Batch-based processing.
• Build a batch data pipeline to ingest, validate, transform, and serve enrollment data from multiple sources.

Key Responsibilities:

• Data ingestion: Design, build, and maintain scalable batch data pipelines to ingest enrollment data from disparate sources using Python, Airflow, and SQL.
• Data quality & validation: Implement robust data validation rules and data quality frameworks to ensure accuracy, consistency, and reliability across all datasets.
• Data transformation: Perform efficient batch data transformations using dbt, Snowflake, and PostgreSQL.
• Historical tracking: Design and maintain historical data tracking (SCD) across datasets.
• Data serving & events: Publish processed data to downstream systems and integrate asynchronous event workflows using Apache Kafka.

Job Requirements:

• Experience: 5+ years of experience as a Data Engineer or Data Platform Engineer.
• Core Tech Stack:Data & Orchestration: Solid experience with Python, Apache Airflow, and dbt.
• Databases & Warehousing: Hands-on experience with Snowflake, PostgreSQL, and advanced SQL.
• Messaging/Events: Experience with Apache Kafka or similar messaging systems.
• Domain & Concept Knowledge: Strong understanding of batch processing architecture, data modeling, and historical data tracking (SCD).
• Language Proficiency: Upper-Intermediate English or higher. Ability to communicate clearly and directly with native English speakers in daily meetings and technical discussions.
• Soft Skills: Self-motivated, strong problem-solving mindset, capable of working independently and taking full ownership in a remote environment.