JioStar
Tech / AI / Software
SeniorDirectorofEngineering,DataPlatforms
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“Senior Director of Engineering, Data Platforms at JioStar. Skills: data engineering strategy, data infrastructure, team leadership, stakeholder management, ML/AI integration. Own and evolve our data engineering strategy. Ensure data quality, availability, and accessibility across the organisation”
What You'll Achieve.
ensuring data engineering becomes a strategic enabler for insights, intelligence, and innovation; ensuring that our team spends time where it matters: enabling analytics, ML, and decision-making at scale; ensuring data drives action
Industry & Context.
What They're Looking For.
Must Have
14+ years of experience in data engineering, 3+ years in a leadership capacity, Proven track record of building reliable, scalable, and cost-conscious data infrastructure, Deep expertise in modern data tooling (e. g. , Snowflake, dbt, Airflow, Kafka, Databricks, etc. ) and cloud-native architectures, Track record of corralling data in a consumer facing application, Experience supporting ML/AI initiatives and integrating data engineering with model development and deployment, understanding of data governance, lineage, observability, and security best practices, Excellent stakeholder management and communication skills, A bias for impact over you know when to ship, when to invest, and when to say “no.
Nice to Have
B-Tech or M-Tech in Computer Science or a related technical discipline from a reputed university
What You'll Do.
Own and evolve our data engineering strategy
and accessibility across the organisation
Optimize data infrastructure and operations for cost-efficiency
Build and lead a high-performing team of data engineers
Partner with data science and ML teams to operationalize models and build AI-ready pipelines and platforms
Serve as the connective tissue between technical and non-technical stakeholders
Run and continuously improve core data programs
and metadata governance
Stay abreast of emerging tools and practices in modern data stacks
Develop and communicate a data engineering roadmap aligned with company goals and future growth
Nurture and grow the next line of awesome leaders
Manage a scale data platform
How You'll Work.
Team & Collaboration
Partner with data science and ML teams; Serve as the connective tissue between technical and non-technical stakeholders; translating needs; aligning priorities; ensuring data drives action
Communication Scope
Excellent stakeholder management and communication skills; comfortable in an exec meeting as in a code review; translating complex technical possibilities into clear business value
Process & Methodology
Develop and communicate a data engineering roadmap
Full Job Description
## Description Job Summary: We are seeking a pragmatic and visionary Head of Data Engineering to lead our data engineering function through its next phase of growth and transformation. This role is not about building pipelines for their own sake—it’s about ensuring data engineering becomes a strategic enabler for insights, intelligence, and innovation. As the steward of our data platform, you will focus on data quality, cost governance, and operational efficiency—ensuring that our data team spends time where it matters: enabling analytics, ML, and decision-making at scale. You will work closely with product, marketing, and C-suite stakeholders, translating complex technical possibilities into clear business value. About the Team: This is a chance to build something enduring. You’ll join a team that values clarity over complexity, outcomes over activity, and learning over ego. Reporting directly to the CTO, you’ll shape how data unlocks value across every function in the company. ## Key Responsibilities Own and evolve our data engineering strategy, balancing pragmatism with forward-thinking architecture. Ensure data quality, availability, and accessibility across the organisation, with clear SLAs and accountability. Optimize data infrastructure and operations for cost-efficiency, scalability, and ease of use. Build and lead a high-performing team of data engineers—instilling a culture of ownership, impact, and curiosity. Partner with data science and ML teams to operationalize models and build AI-ready pipelines and platforms. Serve as the connective tissue between technical and non-technical stakeholders—translating needs, aligning priorities, and ensuring data drives action. Run and continuously improve core data programs, including ETL/ELT, data observability, and metadata governance. Stay abreast of emerging tools and practices in modern data stacks, with a keen sense of what fits versus what dazzles. Develop and communicate a data engineering roadmap aligned
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