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Data Engineer (GCP, Python, SQL)

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Onsite

Data Engineer (GCP, Python, SQL)

Tata Consultancy Services

Data Engineer (GCP, Python, SQL)

Skills

Google Cloud PlatformSQL QueriesPythonData VisualizationJavaData AnalysisScaladbtTerraform

9 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

11 October 2026

What they need


Role- Data Engineer (GCP, Python, SQL)

Desired Experience Range- 6-10years

Location- Bangalore

Must-Have**

  • At least 5+ years work experience including hands-on asData engineer on Google Cloud Platform (GCP)
  • Experience in GCP tools Dataflow and Bigquery
  • Experience in Data Build Tool (DBT)
  • Experience in different data formats (Avro, Parquet)
  • Experience in data query languages (SQL or similar)
  • Experience in data centric programming using one of more programming languages Python, Java /or Scala.
  • Good understanding of different data modelling techniques and trade-off
  • Knowledge of NoSQL and RDBMS databases
  • Have a collaborative and co-creative mindset with excellent communication skills
  • Motivated to work in an environment that allows you to work and take decisions independently
  • Experience in working with data visualization tools
  • Fluent in English both written and verbal

Good to have

  • GCP services (Big query, Pub/sub. data flow, cloud functions), DBT, Terraform. SQL), BQ, DBT, CICD
  • Experience in GCP tools Dataflow, Dataproc and Bigquery
  • Experience in data processing framework Beam, Spark, Hive, Flink
  • Business understanding of retail industry

Role & Responsibilities-

  1. Take end-to-end responsibility to build, optimize and support of existing and new data products towards the defined target vision
  2. Be a champion of DevOps mindset and principles and able to manage CI/CD pipelines and terraform as well as Cloud infrastructure, in our context, it is GCP (Google Cloud Platform).
  3. Ensure that our built data products work as independent units of deployment and non-functional aspects of the data products follow the defined standards for security, scalability, observability, and performance.
  4. Work close to the Product Owner and other stakeholders around vision for existing data products and identifying new data products to support our customer needs
  5. Work with product teams within and outside our domain around topics that relate to the data mesh concept.
  6. Evaluate and drive continuous improvement and reducing technical debt in the teams
  7. Maintain expertise in latest data/analytics and cloud technologies.

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