Sr. Data Engineer

Airtel · Shalimar Bagh

  • Experience6–9 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelsenior
  • Posted2 Sept 2026
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About Airtel

Airtel is hiring in Shalimar Bagh in telecom. This role looks for around 6+ years of experience.

Skills

  • Google Cloud Platform
  • BigQuery
  • SQL
  • Dataform
  • dbt
  • Cloud Composer
  • Apache Airflow
  • Dataflow
  • Apache Beam
  • Dataproc
  • Apache Spark
  • Apache Iceberg
  • data modeling
  • schema design
  • data contracts
  • data quality
  • metadata
  • data lineage
  • observability
  • CI/CD

The role

A data platform engineer at a telecom company designs and operates scalable data-processing solutions using Google Cloud Platform, develops streaming data pipelines, and builds analytical storage with Apache Iceberg. The role also applies Dataform and Apache Airflow to create reusable, orchestrated data frameworks.

Full job description

We are looking for a hands-on Senior Data Engineer to design and build scalable data solutions and reusable data platform capabilities on Google Cloud Platform (GCP). This role combines data engineering and data platform engineering. You will provide technical leadership for complex data-processing capabilities while remaining actively involved in architecture, design, and implementation. You will help define how data products are transformed, orchestrated, governed, and operated at scale, with a strong focus on reusability, automation, performance, reliability, and engineering standards.

Responsibilities:

Own the technical design and architecture of scalable data-processing and transformation solutions on GCP.

Design and build production-grade batch, incremental, and streaming data pipelines.

Develop and optimize complex transformations using BigQuery, SQL, and Dataform/dbt.

Build reusable, metadata-driven, and configuration-driven frameworks that reduce bespoke pipeline development.

Design orchestration patterns using Cloud Composer / Apache Airflow, including dynamic workflows, dependencies, retries, and recovery.

Develop distributed and streaming processing solutions using Dataflow / Apache Beam and Dataproc / Spark.

Define standards for data modeling, schema design, schema evolution, and data contracts.

Design and evolve modern analytical storage patterns, including Apache Iceberg.

Establish engineering patterns for data quality, reconciliation, metadata, lineage, and observability.

Optimize large-scale workloads for performance, scalability, latency, and GCP cost.

Define reusable engineering standards for testing, versioning, CI/CD, and production readiness.