Job description
We are looking for an experienced GCP Data Engineer with strong hands-on expertise in Python, BigQuery, Dataflow, and Cloud Composer. In this role, you will design, build, and maintain scalable data pipelines on Google Cloud Platform (GCP), working closely with business and technology teams to enable reliable data migration, transformation, and analytics use cases.
Roles & Responsibilities
- Design & Develop Data Pipelines
- Design, develop, and maintain scalable, secure, and reliable data pipelinesusing GCP services (BigQuery, Dataflow, Cloud Composer, GCS, etc.).
- Build end-to-end data ingestion and transformation workflows from various source systems (databases, APIs, flat files, etc.).
- Data Migration & Onboarding
- Work with client business and technical teams to build complex data migration pipelinesand seamlessly onboard new data products to the GCP environment.
- Streamline and optimize data migration workflows to add measurable value to client data hubsand analytics platforms.
- Data Transformation & Curation
- Build robust ETL/ELT processes to cleanse, transform, and curate datainto analytics-ready datasets and views.
- Ensure data quality, integrity, and consistency across stages with proper validation, logging, and monitoring.
- Frameworks & Reusability
- Design and build reusable frameworksfor ingesting different data patterns (batch, streaming, CDC, etc.), reducing time-to-market for new data products.
- Create and maintain technical documentationfor pipelines, frameworks, and processes.
- Collaboration & Agile Delivery
- Work in an agile environment, participating in sprint planning, daily stand-ups, and retrospectives.
- Collaborate with data architects, analysts, SMEs, and business stakeholders to translate requirements into scalable data solutions.
- Deployment, CI/CD & Operations
- Use tools like Spinnaker, Jenkins, and Gitto implement CI/CD for data pipelines and related components.
- Deploy and manage data workloads on GKEor other GCP compute services where required.
- Monitor performance, optimize SQL queries and pipeline performance, and troubleshoot issues in production.
Required Experience
- Total Experience:46 years in data engineering / ETL / big data roles.
- Relevant Experience:Minimum 3+ years working on GCP-based data engineeringprojects.
Must-Have Skills (Primary)
- Python (OOPs concept):Strong programming skills with clean, modular, and testable code.
- GCP Data Services:
- Dataflow(or Apache Beam) for building scalable data pipelines.
- Cloud Composer(Airflow) for workflow orchestration and scheduling.
- BigQueryfor data warehousing, analytics, and performance-optimized SQL.
- Strong understanding of ETL/ELT concepts, data integration patterns, and data warehousing fundamentals.
Secondary Skills (Good Working Knowledge)
- Agile methodologies(Scrum/Kanban) working in sprint-based delivery.
- Spinnakerfor deployments in GCP environments.
- Jenkinsfor building CI/CD pipelines.
- Gitversion control and collaborative development.
- GKE (Google Kubernetes Engine)understanding of containerized workloads and orchestration.
Nice-to-Have Skills (Preferred, Not Mandatory)
- Data Modelling Basicsstar/snowflake schemas, dimensional modelling, understanding of fact and dimension tables.
- Tableau Basics– exposure to building or supporting dashboards and BI analytics.
- SQL Performance Tuning– experience optimizing complex queries and improving BigQuery performance.
Educational Qualification
- B.Tech / B.E. / M.Tech / MCA or equivalent degree in Computer Science, IT, Data Engineering, or related fields.
Desired Candidate Profile
- Strong analytical and problem-solving skills with attention to detail.
- Ability to work independently as well as part of a collaborative, cross-functional team.
- Good communication skills to interact with both technical and non-technical stakeholders.
- Proactive mindset with a focus on automation, reusability, and continuous improvement.