Data Engineer (Entity Resolution / Data Engineering)

Role Overview

We are looking for a skilled Data Engineer to build and maintain scalable data pipelines, improve data quality, and develop solutions for record matching and identity resolution. The ideal candidate should have strong experience in Python, SQL, PySpark, Databricks/Snowflake, and modern data engineering practices. You will work with large Business, Consumer, and Healthcare datasets to create accurate, reliable, and high-performing data solutions.

Responsibilities

• Design and develop scalable ETL/ELT data pipelines.
• Process, clean, and transform large datasets.
• Build and maintain data models and databases.
• Perform data deduplication and identity resolution.
• Optimize SQL queries and improve data processing performance.
• Ensure data quality, accuracy, and consistency across multiple sources.
• Develop and maintain workflows using Databricks, Spark, or cloud platforms.
• Collaborate with Data Scientists, Analysts, and Engineering teams.
• Implement data security, governance, and privacy best practices.
• Troubleshoot and resolve data pipeline issues.

Requirements

• Strong experience in Python and Advanced SQL
• Hands-on experience with PySpark
• Experience with Databricks or Snowflake
• Good understanding of ETL/ELT processes
• Experience with Data Modeling and Data Warehousing
• Knowledge of Data Quality and Data Validation
• Experience working with large structured and unstructured datasets
• Familiarity with Git and version control
• Experience with Azure or AWS is preferred