ROLE OVERVIEW

As Manager – Data Engineering, you will lead a team of data engineers and senior software engineers across domains such as data engineering. You will be responsible for defining, building, and optimizing enterprise-grade data platforms and pipelines that support large-scale analytics, AI/ML,

and digital transformation initiatives. In addition, you will manage the Data Engineering Support team,

ensuring reliable production operations through strong incident, problem, and service delivery practices while continuously improving platform stability and performance.

This role requires strong technical leadership in data engineering, deep expertise across modern data stacks, and the ability to balance delivery excellence with people leadership.

Essential Skills Strong

Snowflake data engineering skills (SQL + Snowpark), including incremental processing and operational automation using native capabilities (e.g., pipelines orchestrated with platform features) Proficiency in dbt for modular transformations with built-in testing and documentation practices in a production workflow · Proficient in data visualization using Tableau or Python libraries (e.g., Matplotlib, Seaborn, Plotly) to deliver clear, actionable insights

Experience with AtScale semantic models to standardize KPIs and improve query performance · Solid grasp of data warehousing, lakehouse architecture, and modern analytics on cloud platforms Experience in any relational databases (Oracle, SQL Server, PostgreSQL) and NoSQL databases (MongoDB, Cassandra, DynamoDB) Strong cloud data platform expertise across Snowflake and GCP services (incl. BigQuery and Dataflow) to design and run scalable, production-grade data pipelines

Experience with API development and microservices-based data integrations Proven CI/CD capability for data pipelines, enabling automated build/test/deploy workflows for data transformations and platform changes using modern DataOps practices REQUIREMENT

Roles & Responsibilities:





Define the Data Engineering strategy aligned with organizational data & AI priorities.

Drive adoption of cloud-native data platforms and modern architectures (data lakes, lakehouses, data mesh).

Partner with enterprise teams to enable self-service data and reporting capabilities

Oversee the design, development, and optimization of data pipelines and integrations

Lead delivery of scalable ELT/processing workloads on Snowflake, leveraging platform-native capabilities (e.g., Snowpark) to build performant, maintainable data pipelines

Own implementation of dbt transformation layers (models /tests/ docs) to ensure analytics-ready, version-controlled data products with repeatable deployment practices

Ensure reliable downstream BI consumption by enabling Tableau with governed/published data sources and performance-minded design patterns for enterprise dashboards

Drive adoption and operations of AtScale semantic models to standardize metric definitions and deliver consistent, governed analytics across BI tools and cloud warehouses

Ensure high-quality, reliable, and scalable data infrastructure supporting AI/ML and analytics initiatives

Manage the data platform production support team, establishing clear incident/problem response procedures, escalation paths, and post-incident learnings to protect platform reliability and business SLA Support & Enablement Collaborate with global cross-functional stakeholders to integrate data solutions into enterprise systems

Operationalize data quality gates by embedding validations (e.g., Great Expectations suites / checks) into pipelines so issues are detected early and shared in a common, auditable format for engineering and stakeholders

Promote innovation in data engineering through piloting new tools, techniques, and architectures People Leadership Lead and mentor a diverse team of Sr. Data Engineers and Data Engineers

Foster a culture of collaboration, innovation, and continuous learning Build career pathways and create opportunities for team member’s growth in technical and leadership tracks

📌 Manager - Data Engineering (Chennai)
🏢 HD Supply | Global Technology Center
📍 Chennai