Data Engineer

Data Engineer (Contract)- 5 new contract openings

Location : Onsite 2 days a week

Irving, TX or Hartford, CT - Only

Citizenship : Any (GC/USC will be given preference)

Duration : 6+ months

Data Engineer with 8+ years' experience including 2+ years on GCP, strong in Teradata, BigQuery, Dataflow, Python/Java ETL, and migrating data pipelines to cloud platforms.

We are seeking skilled Data Engineer(s) to support a high-impact enterprise data migration initiative .

The goal is to migrate data warehouse assets and ETL pipelines from Teradata to Google Cloud Platform (GCP).

The role involves hands-on development, testing, and optimization of data pipelines and warehouse structures in GCP , ensuring minimal disruption and maximum performance.

Required Skills:

8 years of experience in Data Engineering , with at least 2 years in GCP.

Strong hands-on experience in Teradata data warehousing , BTEQ , and complex SQL .

Solid knowledge of GCP services : BigQuery, Dataflow, Cloud Storage, Pub/Sub, Composer, and Dataproc.

Experience with ETL/ELT pipelines using custom scripting tools (Python/Java).

Proven ability to refactor and translate legacy logic from Teradata to GCP .

Familiarity with CI/CD, GIT, Argo CD, and DevOps practices in cloud data environments.

Intangibles : Strong analytical, troubleshooting, and communication skills. Problem solving mindset, Attention to detail, Accountability and ownership

Preferred Qualifications

• GCP certification (Preferred: Professional Data Engineer).

• Exposure to Apache Kafka, Cloud Functions, or AI/ML pipelines on GCP.

• Experience working in the healthcare domain.

• Knowledge of data governance, security, and compliance in cloud ecosystems.

• Key Responsibilities:

• Execute migration of data and ETL workflows from Teradata to GCP-based services such as BigQuery, Cloud Storage, Dataflow, Dataproc, and Composer (Airflow).

• Analyze and map existing Teradata workloads to appropriate GCP equivalents.

• Rewrite SQL logic, scripts, and procedures in GCP-compliant formats (e.g., standard SQL for BigQuery).

• Collaborate with data architects and business stakeholders to define migration strategies, validate data quality, and ensure compliance.

• Develop automated workflows for data movement and transformation using GCP-native tools and/or custom scripts (Python).

• Optimize data storage, query performance, and costs in the cloud environment.

• Implement monitoring, logging, and alerting for all migration pipelines and production workloads.