Contract W2 Job Summary We are looking for an experienced Senior Data Engineer with 10+ years of experience in designing, developing, and optimizing scalable data solutions. The ideal candidate should have strong expertise in ETL/ELT, SQL, Python, cloud platforms, data warehousing, data pipelines, and data modeling . Key Responsibilities Design, develop, and maintain scalable ETL/ELT data pipelines . Build and optimize data solutions using Python, PySpark, and SQL . Develop enterprise data warehouses, data lakes, and analytical platforms . Work with cloud technologies such as AWS, Azure, or Google Cloud Platform . Design and implement data models , including dimensional and transactional models. Develop data pipelines using tools such as Informatica, Dataflow, Databricks, AWS Glue, or Azure Data Factory . Implement data quality, validation, governance, and performance optimization processes. Work with databases such as Oracle, Postgre
SQL, SQL
Server, Teradata, Snowflake, and BigQuery . Collaborate with architects, analysts, developers, and business teams to define data requirements. Troubleshoot data pipeline failures and resolve performance and production issues. Mentor junior and mid-level data engineers and provide technical guidance. Participate in architecture, code reviews, documentation, and deployment activities. Required Skills 10+ years of experience in Data Engineering. Strong hands-on experience with SQL, Python, and PySpark . Strong knowledge of ETL/ELT development and data pipeline architecture . Experience with AWS, Azure, or Google Cloud Platform cloud environments. Strong understanding of Data Warehousing, Data Lakes, and Lakehouse architecture . Experience with Snowflake, BigQuery, Databricks, Redshift, or similar platforms . Strong knowledge of data modeling and database concepts . Experience with Git, CI/CD, and Agile methodologies . Excellent analytical, problem-solving, and communication skills. Experience leading technical discussions and mentoring team members.
