Senior Data Engineer

Groupm Media; Gurugram District, Bengaluru; Hybrid; INR 2,800,000 - 4,000,000; Full time

Job summary

GroupM Media is seeking a Senior Data Engineer to act as the technical authority for offshore delivery teams, directing complex data engineering solutions and overseeing critical data pipelines across large-scale media datasets. The role focuses on modernizing platforms with ADF, SQL optimization, and automated DevOps practices.

The candidate will mentor engineers, collaborate with US onshore leadership, and champion governance, documentation, and scalable data architectures for enterprise-grade

Qualifications

• 3–4 years of progressive experience in data engineering.

Responsibilities

• Design, develop, and optimize enterprise ETL/ELT pipelines using Azure Data Factory and Azure Data Lake Storage.
• Implement efficient SQL solutions including partitioning and indexing for analytics models.
• Lead automation frameworks using Python and API orchestration to streamline data lifecycle.
• Own production pipeline reliability through root-cause analysis and long-term stability measures.
• Establish coding standards via code reviews and technical audits for offshore engineering teams.
• Document data lineage and automated CI/CD deployment practices for governance.

Skills

Azure Data Factory

SQL

Python

CI/CD automation

Tools

Azure DevOps

Git

Databricks

DBT

Terraform

Job description

Senior Data Engineer

Role Summary

The Senior Data Engineer acts as the technical authority within the offshore delivery team, setting strategic direction for complex data engineering solutions and overseeing mission-critical data pipelines across large-scale media and datasets. This role is responsible for architecting, optimizing, and governing advanced data platforms, while mentoring engineers and collaborating closely with US onshore leadership to deliver enterprise-grade, scalable solutions. The position demands exceptional technical acumen in Azure Data Factory (ADF) and Azure T-SQL, with a focus on innovation, automation, and operational excellence.

Key Responsibilities:

• Design, develop, and optimize enterprise ETL/ELT pipelines utilizing Azure Data Factory, Azure Data Lake Storage, and advanced serverless technologiesensuring cross-platform scalability, security, and reliability.
• Implement highly efficient, complex SQL solutions—including advanced query optimization, partitioning, and indexing to power sophisticated analytics models and enable real-time data processing.
• Lead the development and integration of robust automation frameworks using Python, and API orchestration, introducing innovative solutions to streamline the entire data lifecycle and maximize operational efficiency.
• Exercise full ownership of production pipeline reliability; proactively identify and resolve critical issues through deep root-cause analysis, and institute resilient, long-term stability measures for continuous uptime.
• Establish, refine, and enforce rigorous coding and architectural standards through comprehensive code reviews and technical audits, setting quality benchmarks for the offshore engineering team.
• Champion best-in-class documentation, data lineage, and automated CI/CD deployment practices, ensuring transparency, auditability, and governance across all data assets.
• Demonstrate expert-level support for analytics and media teams, translating business challenges into scalable, high-performance technical solutions, leveraging deep Azure and SQL expertise.

Senior-Level Expectations:

• Act as the organization’s subject matter expert (SME) in end-to-end pipeline architecture, orchestration frameworks, schema evolution, and advanced Azure Data Factory strategies.
• Lead modernization initiatives across the organization, championing the adoption of technologies such as Databricks, DBT and advanced DevOps practices to future-proof the data platform and enable rapid innovation.
• Ensure strict adherence to SLAs and regulatory compliance through advanced monitoring, proactive risk mitigation, and continuous improvement of operational processes.

Required Skills

• 3-4 years of progressive experience in data engineering, with expert-level mastery of Azure Data Factory, SQL, and cloud data platforms (Azure and/or GCP).
• Proven expertise in designing, optimizing, and managing large-scale, production-grade data pipelines, including deep skills in SQL performance tuning, ADF orchestration, and CI/CD automation.
• Advanced knowledge of production operations, troubleshooting, and high-availability data processing at scale.

Good to Have

• Adverity
• Dataflow
• Big Query
• Databricks
• DBT
• Terraform
• Wrike/Jira/Azure DevOps
• DP203 / GCP Data Engineer certifications