Associate Director, Data Engineering - India

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Associate Director, Data Engineering - India

This role is Office Based, Pune Office

Associate Director Data Engineering

Location : Pune, India

The Associate Director, Data Engineering will serve as a strategic leader within our Data & Analytics team, responsible for the development and delivery of scalable, secure, and high-performance data pipelines and analytical models. This individual will play a critical role in shaping the enterprise data ecosystem, driving innovation across analytics and data integration initiatives, and ensuring operational excellence in data engineering practices.

You will lead a global team of data engineers to support enterprise-wide analytics across Sales, Marketing, Services, Customer Success, Finance, HR, Product, and Engineering. As a technical leader, you will balance hands-on contributions with strategic direction, governance, and execution oversight. You’ll collaborate closely with enterprise architects, data & reporting analysts, data scientists, and business stakeholders to enable actionable insights and build a modern data infrastructure that supports our company’s growth.

This role goes beyond traditional BI—it includes developing predictive models, uncovering insights with Gen AI-powered features to drive data driven decision making . You’ll use tools like Python, Snowflake Cortex , alongside SQL, DBT, Air Flow, and Snowflake to deliver scalable solutions that influence strategy and execution across the enterprise.

In this role, you will...

• Provide strategic and technical leadership to the data engineering function, including architecture, development, quality, and delivery of data solutions.
• Lead and mentor a global team of engineers to build and support robust, performant data pipelines using Snowflake, DBT, Python, and AWS-based infrastructure.
• Partner with Business Stakeholders, Data Governance, and IT teams to define and execute a multi-year roadmap for data platform modernization and analytics enablement.
• Own the ETL / ELT development lifecycle—including design, orchestration, configuration, automation, testing, and support—ensuring adherence to SDLC, architectural standards, and security practices.
• Establish and enforce scalable best practices for data ingestion, transformation, modeling, documentation, and operational support.
• Define current and future state BI and data engineering architectures to support enterprise reporting, self-service analytics, and advanced data science use cases.
• Drive adoption of modern tools, techniques, and reusable frameworks that increase engineering velocity and reliability (, CI / CD for data pipelines, automated testing, monitoring).
• Proactively identify areas for data quality, performance, and process improvement across the data pipeline ecosystem, lead remediation efforts.
• Act as an escalation point for complex production issues and strategic project deliverables.
• Serve as a technical thought leader and advocate for data engineering practices across the organization.

You have what it takes if you have...

Extra dose of awesome if you have...

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