Company : Deutsche Telekom Digital Labs, Gurgaon

Deutsche Telekom Digital Labs is the captive technology unit of Deutsche Telekom, building scalable digital platforms and products for customers across Europe.

Role : Data Engineer II GCP Data Platform

Objective of the Role :

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.

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.

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

You Will :

- Design, develop and maintain production-grade data pipelines on Google Cloud Platform.
- Build scalable batch and incremental data-processing solutions.
- Develop complex transformations using BigQuery, SQL and Dataform / dbt.
- Build and maintain data-processing workflows using Cloud Composer / Apache Airflow.
- Develop reusable transformation components, orchestration patterns, libraries and templates.
- Implement metadata-driven and configuration-driven processing where appropriate.
- Build distributed data-processing solutions using Dataflow / Apache Beam and/or Dataproc / Spark.
- Design data models for analytical and downstream data-product requirements.
- Implement incremental and idempotent processing patterns.
- Define and maintain schemas and data contracts.
- Implement automated data-quality checks, validation and reconciliation.
- Capture and integrate metadata and lineage into data-processing workflows.
- Optimise BigQuery queries and pipelines for performance and cloud cost.




- Implement automated testing and integrate data workloads with CI/CD pipelines.
- Build monitoring and operational controls for production pipelines.
- Troubleshoot production issues and perform root-cause analysis.
- Contribute to reusable data-platform capabilities and engineering standards.
- Collaborate with Data Engineers, Platform Engineers, DevOps, Architects and business stakeholders.

You Must Have :

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




- Experience troubleshooting and supporting production data pipelines.
- Ability to independently design solutions rather than only implement predefined specifications.

Technical Skills :

Cloud & Storage :

- Google Cloud Platform
- BigQuery
- Google Cloud Storage

Transformation & Orchestration :

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

Data Processing :

- Dataflow / Apache Beam
- Dataproc / Spark / PySpark

Programming & Engineering :

- Python
- Git
- Automated testing
- CI/CD
- Monitoring and troubleshooting

Data Engineering Capabilities :

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

Good to Have :

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

Strong Interpersonal Skills :

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

📌 Data Engineer II - Google Cloud Platform (India)
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