Roles & Responsibilities:

• Design and implement reliable data pipelines to integrate disparate data sources into a single Data Lakehouse
• Design and implement data quality pipelines to ensure data correctness and building trusted datasets
• Design and implement a Data Lakehouse solution which accurately reflects business operations
• Assist with data platform performance tuning and physical data model support including partitioning and compaction
• Provide guidance in data visualizations and reporting efforts to ensure solutions are aligned to business objectives

Qualifications:

• 5+ years of experience as a Data Engineer designing and maintaining data pipeline architectures
• 5+ years of programming experience in Python, ANSI SQL, PLSQL, and TSQL
• Experience in various data integration patterns including ETL, ELT, Pub/Sub, and Change Data Capture
• Experience with common Python Data Engineering packages including pandas, Numpy, Pyarrow Pytest, Scikit-Learn, and Boto3
• Experience in software development practices such as Design Principles and Patterns, Testing, Refactoring, CI/CD, and version control
• Experience in implementing a Data Lakehouse using Apache Iceberg or Delta Lake
• Knowledgeable of modern data platform technologies including Apache Airflow, Kubernetes, and S3 Object Storage
• Experience with Dremio and Airbyte is preferred

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