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 strong 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.