JioStar

Director - Data Engineering and platforms

Bengaluru · Director

Older listing - lower visibility likelyVerified listingPosted 257d ago

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Sprint PlanningDependency ManagementCloud InfrastructureSystems ThinkingStewardshipEconomicsAWS Elastic MapReduce (EMR)SQL (Programming Language)

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Job description

Role Summary: As a Director of Data Engineering and Platforms, you will lead and scale high-performing engineering teams responsible for building and operating JioHotStar’s mission‑critical data infrastructure. Your teams power platforms that handle hundreds of millions of requests per minute, process billions of real‑time events daily, and manage petabyte‑scale data systems that directly enable media streaming, personalization, analytics, and AI‑driven experiences. This role blends people leadership, technical depth, delivery ownership, and strategic influence. You will be accountable for execution excellence, system reliability, cost efficiency, and growing engineers into strong technical leaders—while partnering closely with Product, Data Science, AI, and Business stakeholders.

About the team: The Data Platforms team at JioHotStar builds the foundational data systems that power next‑generation media experiences, AI‑powered products, and autonomous agents. Beyond traditional data engineering, the team enables AI/ML pipelines, MCP infrastructure, and real‑time intelligence that operate at massive scale across live sports, video streaming, and digital platforms. As an Engineering Manager, you will help shape the platform roadmap, scale the organization, and ensure the team consistently delivers resilient, secure, and future‑ready systems.

Key Responsibilities:

People & Team Leadership: Lead, hire, mentor, and grow high-performing data platform engineering teams while fostering a culture of ownership, accountability, and engineering excellence.

Technical & Architectural Stewardship: Provide technical direction and architectural oversight for large-scale, real-time data platforms supporting media streaming, analytics, and AI/ML workloads.

Execution & Delivery Ownership: Own end-to-end delivery of platform initiatives, ensuring predictable execution, high system reliability, and operational excellence at scale.

Cross-Functional Partnership: Partner with Product, AI/ML, Analytics, and Business stakeholders to translate business goals into scalable platform outcomes.

Platform Economics & Impact: Drive cost efficiency, scalability, and data governance while improving time-to-insight and business decision-making.

Technical & Architectural Leadership

Provide technical direction and architectural oversight for large‑scale data systems

Review and guide system designs, trade‑offs, and long‑term platform decisions

Ensure data platforms support AI/ML workloads, MCP services, and real‑time personalization

Balance hands‑on technical involvement with effective delegation

Champion best practices in distributed systems, reliability, security, and data governance

Delivery & Execution Ownership:

Own end‑to‑end delivery for platform initiatives—from planning to production

Translate business and product requirements into clear technical roadmaps and milestones

Ensure predictable execution through sprint planning, prioritization, and dependency management

Drive operational excellence: monitoring, incident management, SLAs, and post‑mortems

Continuously improve developer productivity, system stability, and release velocity

Cross‑Functional & Stakeholder Collaboration:

Partner closely with Product, Analytics, AI/ML, Media Tech, and Business teams

Act as the primary technical and delivery interface for senior stakeholders

Influence platform strategy through data‑driven insights and clear communication

Ensure data is trusted, discoverable, and accessible across the organization

Platform Economics & Business Impact:

Own cost efficiency and unit economics across ingestion, storage, and processing layers

Drive optimization initiatives for cloud infrastructure and tooling

Ensure platforms reduce time‑to‑insight and improve business decision‑making

Balance innovation with operational sustainability at scale

Skills and attributes for success:

Leadership & Management: Proven ability to lead and scale senior engineering teams, coach talent, and manage performance in fast-paced environments.

Technical Depth: Strong understanding of distributed data systems, streaming architectures, cloud platforms, and data foundations for AI/ML.

Execution Excellence: Demonstrated ownership of complex platform deliveries with a strong bias toward reliability, observability, and continuous improvement.

Systems Thinking: Ability to evaluate architectural trade-offs and guide teams toward sustainable, long-term solutions.

Communication & Influence: Clear communicator who can influence technical and non-technical stakeholders and drive alignment across teams.

Technical Expertise (Depth + Breadth):

Strong understanding of real‑time and batch data architectures

Hands‑on experience with distributed processing frameworks (Spark, Flink, or equivalent)

Deep familiarity with Kafka/Kinesis, event‑driven systems, and streaming pipelines

Cloud expertise with AWS (S3, EMR, Kinesis, Glue, Redshift, etc.) or equivalent

Strong grasp of data lakes, warehousing, and modern table formats (Iceberg, Delta, Hudi)

Experience supporting AI/ML data pipelines, feature stores, and training workflows

Solid grounding in databases, data modeling, and SQL

Leadership & Communication:

Ability to communicate complex technical concepts to non‑technical stakeholders

Strong decision‑making skills with a bias for action and long‑term thinking

Experience influencing architecture and roadmap beyond your immediate team

Passion for building inclusive, diverse, and high‑impact teams

Preferred Education & Experience:

B-Tech or M-Tech in Computer Science or a related technical discipline from a reputed university.

12+ years of experience in data engineering, with 5+ years in a leadership capacity.

Experience leading multi‑team or platform‑wide initiatives

Prior exposure to media streaming, ad‑tech, personalization, or AI platforms

Track record of scaling teams and systems during periods of rapid growth

About Us

Perched firmly at the nucleus of spellbinding content and innovative technology, JioStar is a leading global media & entertainment company that is reimagining the way audiences consume entertainment and sports. Its television network and streaming service together reach more than 750 million viewers every week, igniting the dreams and aspirations of hundreds of million people across geographies.

JioStar is an equal opportunity employer. The company values diversity and its mission is to create a workplace where everyone can bring their authentic selves to work. The company ensures that the work environment is free from any discrimination against persons with disabilities, gender, gender identity and any other characteristics or status that is legally protected

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Director - Data Engineering and platforms

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