Description

You will design and implement scalable data architectures and end-to-end data pipelines.

Responsibilities

• Define and implement data architecture and design features within the existing Data Warehouse.
• Design, implement, and update both new and existing batch ETL pipelines.
• Partner with engineering, product, and analytics teams to build reliable, trusted datasets.
• Lead the development of data-driven projects and establish connections between technical and data science teams.
• Automate and monitor data processes using orchestration tools.

Required Skills

• 8+ years of experience in data engineering and architecture.
• Expertise in data modeling paradigms including Kimball, Inmon, Data Marts, Data Vault, or Medallion.
• Hands-on experience designing data platforms on AWS for batch and stream processing.
• Proficiency with AWS services including EMR, Glue, S3, Kinesis, DynamoDB, and ECS.
• Deep understanding of Apache Spark and SQL.
• Ability to develop backend services in Python to enable data pipelines.
• Expertise in designing ETL pipelines using a combination of Python and SQL.
• Strong knowledge of data ingestion, transformation, and data quality processes.
• Degree in any graduate field.

Preferred Skills

• Experience with Data Lakehouse storage formats such as Delta, Iceberg, or Hudi.
• Knowledge of Python libraries like Pandas, Polars, or DuckDB.
• Experience with Azure, Databricks, Snowflake, Tableau, or PowerBI.

Key Skills

Education

Any Graduate