Senior Data Engineer

About this role

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Skills you'll use

Who can apply

• 5+ Years in Data Engineering: You’ve lived through the "on-call" life and know how to build systems that don't break at 3 AM.
• The Power Trio: Expert-level proficiency in Python, SQL, and PySpark.
• Modern Lakehouse Stack: Hands-on experience with Databricks (Delta Lake) or Snowflake. You understand the nuances of the Medallion Architecture (Bronze/Silver/Gold).
• Transformation & Modeling: Advanced experience with dbt (Data Build Tool). You treat data models like software, including version control, testing, and documentation.
• Orchestration: Experience with Apache Airflow or Prefect, specifically building complex, idempotent DAGs.
• Streaming Experience: Familiarity with Kafka, Kinesis, or Spark Streaming is a huge plus—our BPO operations move in real-time.
• Infrastructure as Code (IaC): Comfort with Terraform or CloudFormation to manage your own data infrastructure.
• In-Process Analytics (DuckDB): Proven experience using DuckDB for high-speed local development, unit testing data transformations, or as a query engine for "small-to-medium" datasets (up to 100GB) without the overhead of a distributed cluster.
• Hybrid Execution Patterns: Ability to identify when to use heavyweight compute (PySpark/Databricks) versus lightweight compute (DuckDB/Python) to minimize cloud costs and reduce job latency.
• Parquet/Iceberg Interaction: Experience using DuckDB to directly query data stored in S3/Azure Blob (via Parquet or Iceberg files) for rapid ad-hoc analysis or local dashboarding.

About TaskUs

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