Senior Data Engineer [GCP & BigQuery] [Only W2]

⚠️ Please Note: This role is NOT open for C2C. Only W2 candidates will be considered.

Position: Senior Data Engineer

Location: Remote

Duration: 6 Months Contract to Hire

Job Summary:

We are seeking a Senior Data Engineer with strong hands-on experience in Google Cloud Platform (GCP), BigQuery, Python, and SQL. The role focuses on building and maintaining cloud-based data pipelines, data warehousing, data modeling, and improving data performance. The ideal candidate should have strong troubleshooting skills, take ownership of technical solutions, and work closely with business and technical teams. Excellent communication skills are essential to explain technical requirements and collaborate across teams.

Must-Have Skills:

• 6+ years of experience with SQL and Relational Database Management Systems (RDBMS).
• 4+ years of hands-on experience with Google Cloud Platform (GCP).
• 3+ years of experience with Google BigQuery.
• Strong programming experience with Python, SQL, and PySpark.
• Experience implementing and supporting GCP/Azure cloud-based services.
• Hands-on experience with dimensional data modeling, schema design, and data warehousing.
• Strong data troubleshooting and performance optimization skills.
• Experience identifying process improvements and implementing best practices.
• Ability to take ownership and work in a fast-paced, collaborative environment.
• Excellent written and verbal communication skills, including working with cross-functional business teams.

Nice-to-Have Skills:

• Apache Airflow for data pipeline orchestration.
• Databricks experience.
• Microsoft Azure experience.
• Healthcare industry experience.

Responsibilities:

• Design, develop, and maintain cloud-based data pipelines using GCP, BigQuery, Python, and SQL.
• Build and optimize data models, database schemas, and data warehousing solutions.
• Develop and modify SQL, Python, and PySpark code to support cloud-based data services.
• Troubleshoot data issues and implement performance improvements.
• Collaborate with business and technical teams to understand requirements and communicate solutions effectively.
• Take ownership of data engineering solutions, improve existing processes, and implement best practices.