Google Cloud Platform Data Engineer

Job Title: Google Cloud Platform Data Engineer

Location: Hartford, CT (Hybrid)

Duration: Contract

Job description:

Mandatory Skills

Design, build, and maintain scalable data pipelines using Cloud Dataflow, Apache Beam, Apache Spark, or BigQuery.

Develop ETL/ELT workflows for data ingestion, transformation, and processing using Cloud Composer (Airflow), TIDAL, Dataform, or custom scripts.

Optimize BigQuery performance through partitioning, clustering, and query tuning.

Implement data governance, security, and compliance best practices within Google Cloud Platform.

Work with Cloud Storage, Pub/Sub,Ni-Fi, Cloud SQL and Bigtable for real-time and batch data processing.

Monitor and troubleshoot data pipeline performance, failures, and cost efficiency.

Collaborate with data scientists, analysts, and software engineers to support business requirements.

Ensure data quality, validation, and integrity using appropriate testing frameworks.

Strong expertise in Google Cloud Platform services (BigQuery, Dataflow, Cloud Storage, Pub/Sub, Bigtable, Firestore, etc.).

Proficiency in SQL, Python, and Java for data processing and automation.

Experience with ETL/ELT workflows using Cloud Composer, Dataflow, or Dataform.

Strong understanding of data modeling, warehousing, and distributed computing.

Experience with real-time and batch processing architectures.

Knowledge of CI/CD pipelines, Git, and DevOps best practices.

Understanding of security and compliance standards (IAM, encryption, GDPR, HIPAA, etc.).

Preferred Qualifications:

Google Cloud Platform certifications (e.g., Professional Data Engineer, Associate Cloud Engineer).

Experience with machine learning pipelines on Google Cloud Platform (Vertex AI, AI Platform, etc.).

Exposure to Kafka, Ni-Fi, or other streaming technologies.

Experience with containerization and orchestration (Docker, Kubernetes, GKE).