Manager - Data Engineering

HD Supply; Chennai District; On-site; INR 1,500,000 - 2,200,000; Full time

Job summary

HD Supply seeks a Data Engineering leader based in Chennai, India, to define the Data Engineering strategy and oversee the development of data pipelines. Candidates should have 9 to 14 years of experience, including leadership in delivering scalable ELT solutions on Snowflake.

The role involves collaboration with teams to enhance self-service data and ensure relevant data quality across systems. Ideal candidates will have strong expertise in cloud platforms and data warehousing architectures.

Qualifications

• 9 - 14 years of experience with leadership in data platform support.
• Proven experience in designing enterprise data engineering solutions.
• Strong cloud expertise with Snowflake and GCP services.

Responsibilities

• Define the Data Engineering strategy aligned with organizational priorities.
• Oversee the design, development, and optimization of data pipelines.
• Lead delivery of scalable ELT workloads on Snowflake.

Skills

Expertise in Snowflake ELT patterns

Strong cloud data platform expertise

Proficiency in dbt for modular transformations

Experience enabling analytics consumption via Tableau

Strong grasp of data warehousing

Experience with API development

Proficient in data visualization using Python

Experience with incremental processing

Job description

Role & 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 SLAs
• 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
• 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 members growth in technical and leadership tracks.

Preferred candidate profile

• 9 -14 years of progressive experience, including 3-4 years of relevant leadership experience in end-to-end technical delivery and data platform support/operations for business-critical systems
• Proven experience in designing and delivering data engineering solutions at enterprise scale
• Expertise in Snowflake ELT patterns including incremental processing (Streams), orchestration (Tasks), ingestion/loading, and Snowpark (Python) for scalable transformations and pipeline automation
• Experience enabling analytics consumption via Tableau (published datasets, performance support)
• Experience delivering production transformations using dbt (models, tests, docs, CI/CD)
• 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
• Strong 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