Data Engineer II

We are looking for a hands-on Data Engineer II with strong GCP experience to build scalable data pipelines, transformations, and reusable data-platform capabilities. The role involves taking solutions end-to-end from design and development to testing, deployment, and production support while building reliable and reusable data engineering solutions.

Responsibilities:

• Design, develop, and maintain production-grade data pipelines on GCP.
• Build scalable batch and incremental processing solutions.
• Develop complex transformations using BigQuery, SQL, and Dataform/dbt.
• Build and maintain workflows using Cloud Composer / Apache Airflow.
• Develop reusable transformation components, frameworks, and orchestration patterns.
• Build distributed data-processing solutions using Dataflow / Apache Beam and/or Dataproc / Spark.
• Design data models for analytical and downstream data products.
• Implement data-quality checks, validation, reconciliation, and data lineage.
• Optimize pipelines and BigQuery workloads for performance and cloud cost.
• Implement automated testing and integrate data workloads with CI/CD.
• Monitor production pipelines and troubleshoot issues through root-cause analysis.
• Collaborate with data engineering, platform engineering, DevOps, architecture, and business teams.

Requirements:

• 4+ years of hands-on data engineering experience.
• Strong hands-on experience with GCP and BigQuery.
• Advanced SQL; complex joins, CTEs, window functions, and query optimization.
• Strong Python development skills.
• Experience with production ETL/ELT pipelines.
• Hands-on experience with Cloud Composer / Apache Airflow.
• Experience with Dataform and/or dbt.
• Experience with Dataflow / Apache Beam or Dataproc / Spark / PySpark.
• Strong understanding of data modelling and large-scale datasets.
• Experience with incremental and idempotent processing.
• Understanding of data contracts, schema evolution, data quality, and reconciliation.
• Experience with Git, automated testing, and CI/CD.
• Strong production troubleshooting and problem-solving skills.

Technical Skills:

• Cloud: GCP, BigQuery, Google Cloud Storage.
• Programming: Python, SQL.
• Data Processing: Dataflow, Apache Beam, Dataproc, Spark/PySpark.
• Orchestration: Cloud Composer, Apache Airflow.
• Transformation: Dataform, dbt.
• Engineering: Git, CI/CD, Automated Testing, Monitoring.
• Data Engineering: ETL/ELT, Batch Processing, Data Modelling, Data Quality, Data Contracts, Metadata, and Lineage.

Good to Have:

• Apache Iceberg or modern lakehouse technologies.
• Streaming or event-driven processing.
• Data Product / Data Mesh concepts.
• Metadata-driven or configuration-driven processing.
• Change Data Capture (CDC).
• Terraform / Infrastructure as Code.
• Experience building reusable components for multiple engineering teams.
• A strong ownership mindset, good analytical and debugging skills, the ability to independently design solutions, and the confidence to take data engineering solutions through production.