Job Description

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Role: Data Engineer II – GCP Data Platform

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Objective of the Role

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We are looking for a hands-on Data Engineer II with strong Google Cloud Platform experience to build scalable data pipelines, transformations and reusable data-platform capabilities.

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You will work across Data Engineering and Data Platform Engineering , independently delivering production-grade data products while contributing reusable components and engineering patterns that can be adopted across multiple teams and use cases.

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The role requires strong hands-on development skills and the ability to take a solution from design through implementation, testing, deployment and production support.

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You Will

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- Design, develop and maintain production-grade data pipelines on Google Cloud Platform .
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- Build scalable batch and incremental data-processing solutions .
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- Develop complex transformations using BigQuery, SQL and Dataform / dbt .
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- Build and maintain data-processing workflows using Cloud Composer / Apache Airflow .
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- Develop reusable transformation components, orchestration patterns, libraries and templates.
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- Implement metadata-driven and configuration-driven processing where appropriate.
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- Build distributed data-processing solutions using Dataflow / Apache Beam and/or Dataproc / Spark .
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- Design data models for analytical and downstream data-product requirements.
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- Implement incremental and idempotent processing patterns.
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- Define and maintain schemas and data contracts.
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- Implement automated data-quality checks, validation and reconciliation.
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- Capture and integrate metadata and lineage into data-processing workflows.
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- Optimise BigQuery queries and pipelines for performance and cloud cost.
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- Implement automated testing and integrate data workloads with CI/CD pipelines.
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- Build monitoring and operational controls for production pipelines.
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- Troubleshoot production issues and perform root-cause analysis.
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- Contribute to reusable data-platform capabilities and engineering standards.
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- Collaborate with Data Engineers, Platform Engineers, DevOps, Architects and business stakeholders.
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You Must Have

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- 4+ years of hands-on Data Engineering experience building production data solutions.
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- Strong practical experience with Google Cloud Platform (GCP) .
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- Strong hands-on experience with BigQuery .
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- Advanced SQL skills including complex joins, CTEs, window functions and query tuning.
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- Strong Python development skills for data processing, automation and testing.
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- Experience developing production ETL / ELT pipelines .
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- Hands-on experience with Cloud Composer / Apache Airflow .
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- Experience with Dataform and/or dbt .
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- Experience designing batch and incremental processing pipelines.
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- Experience with Dataflow / Apache Beam or Dataproc / Spark / PySpark .
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- Robust understanding of data modelling, including normalization, denormalization and dimensional modelling.
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- Experience working with large-scale datasets.
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- Experience with incremental and idempotent pipeline patterns.
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- Understanding of data contracts and schema evolution.
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- Experience implementing data-quality validation and reconciliation.
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- Understanding of metadata and data lineage.
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- Experience with Git, automated testing and CI/CD .
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- Experience troubleshooting and supporting production data pipelines.
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- Ability to independently design solutions rather than only implement predefined specifications.
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Technical Skills

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Cloud & Storage

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- Google Cloud Platform
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- BigQuery
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- Google Cloud Storage
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Transformation & Orchestration

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- Advanced SQL
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- Dataform / dbt
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- Cloud Composer / Apache Airflow
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Data Processing

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- Dataflow / Apache Beam
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- Dataproc / Spark / PySpark
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Programming & Engineering

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- Python
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- Git
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- Automated testing
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- CI/CD
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- Monitoring and troubleshooting
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Data Engineering Capabilities

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- ETL / ELT
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- Batch processing
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- Incremental and idempotent pipelines
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- Data modelling
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- Data contracts
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- Data quality and reconciliation
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- Metadata and lineage
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- Query performance optimisation
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- Cloud-cost optimisation
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- Reusable data-platform components
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Good to Have

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- Experience with Apache Iceberg or modern lakehouse table formats.
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- Experience with streaming or event-driven processing.
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- Practical understanding of Data Product / Data Mesh principles .
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- Experience with metadata-driven or configuration-driven processing.
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- Experience with Change Data Capture.
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- Familiarity with Terraform / Infrastructure as Code .
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- Experience building reusable components used by multiple engineering teams.
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Strong Interpersonal Skills

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- Strong ownership mindset and ability to take engineering work through production.
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- Solid analytical, debugging and problem-solving skills.
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- Ability to communicate technical decisions clearly.
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- Comfortable participating in design and code reviews.
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- Ability to collaborate with engineering and business stakeholders.
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- Ability to work independently while seeking guidance for complex architectural decisions.
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- Comfortable working within distributed and multicultural teams.
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📌 Data Engineer (Gurugram)
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