WHO YOU’LL WORK WITH
You will be part of Nike’s Global Technology organization, working within the India Tech Centre in Bangalore, India to support Consumer Product & Innovation capabilities. You will report to the Engineering Director and partner closely with product managers, principal engineers, architects, data engineers, data science, security, platform and business stakeholders. You will lead a team of data engineers and collaborate with local and global teams to deliver reliable, scalable and secure data platforms that enable analytics, reporting, AI/ML and business decision-making.
WHO WE ARE LOOKING FOR
We are looking for an experienced Data Engineering Manager to lead, coach and grow a high-performing engineering team in Bengaluru. In this role, you will own the strategy, architecture and execution of enterprise data platform capabilities that power analytics, reporting, AI/ML and business decision-making. You will combine technical depth with people leadership, delivery ownership and strong cross-functional collaboration. The ideal candidate has proven experience building production-grade data pipelines, modern cloud data platforms and data governance practices, while developing engineers and partnering with stakeholders to deliver measurable business outcomes.
WHAT YOU’LL WORK ON
As Manager, Data Engineering, you will lead the design, build and operation of enterprise-scale data platforms, including lakehouse, data warehouse, ingestion, transformation, orchestration and integration capabilities. You will guide the team in delivering reliable batch and real-time data pipelines, improving data quality and observability, enabling AI/ML-ready data products, and driving engineering best practices such as automation, testing, monitoring, documentation and CI/CD. You will also manage priorities, delivery cadence, technical roadmap, resource planning and stakeholder alignment across local and global teams.
Key Responsibilities
Lead, mentor, recruit and grow a high-performing team of data engineers, fostering a culture of technical excellence, collaboration and continuous improvement.
Define and execute the technical roadmap for enterprise data platform capabilities, aligning priorities with product, architecture and business strategy.
Design, build and operate scalable, fault-tolerant data pipelines and ETL/ELT frameworks that support batch, streaming and near-real-time data processing.
Architect and evolve data lakehouse, data warehouse, ingestion, transformation and integration layers using modern cloud-native technologies.
Oversee data quality, observability, metadata, governance, privacy and security standards across platform components and data products.
Partner with product management, software engineering, analytics, data science, architecture, security and business stakeholders to understand needs and deliver analytics-ready data solutions.
Enable AI/ML-ready data architecture, including reusable data products, feature engineering workflows and reliable data services for advanced analytics.
Drive DataOps and engineering best practices including CI/CD, automated testing, monitoring, alerting, documentation, performance optimisation and cost efficiency.
Manage backlog prioritisation, sprint planning, delivery cadence, stakeholder communication and operational stability for the data platform team.
Evaluate, recommend and implement new tools, frameworks and technologies that improve platform reliability, scalability, developer productivity and business value.
Qualifications Required
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Mathematics or a related technical field, or equivalent practical experience.
10+ years of hands-on experience in data engineering, including experience building and operating production-grade pipelines and data platforms at scale.
3+ years of people leadership experience, including hiring, coaching, mentoring, performance management and development of technical teams.
Strong proficiency in SQL, Python and distributed data processing frameworks such as Spark or PySpark.
Deep expertise in data warehousing, lakehouse architectures, data modelling, ETL/ELT design and large-scale data integration patterns.
Experience with cloud data platforms and services such as AWS, Snowflake, Databricks or equivalent technologies.
Experience with orchestration, transformation and streaming technologies such as Apache Airflow, dbt, Kafka or Kinesis.
Solid understanding of data governance, metadata management, data cataloguing, privacy, security, data quality and observability practices.
Experience enabling analytics and AI/ML use cases through reliable data products, feature engineering workflows and reproducible data pipelines.
Excellent problem-solving, communication and stakeholder management skills, with the ability to translate technical concepts for non-technical audiences.
Preferred
Experience working in a globally distributed engineering organisation and partnering with stakeholders across regions.
Hands-on experience with data mesh, data product thinking, feature stores, real-time analytics platforms or modern lakehouse architectures.
Familiarity with infrastructure-as-code, containerisation and platform engineering practices such as Terraform, CloudFormation, Docker or Kubernetes.
Experience managing cloud infrastructure usage, platform reliability, performance optimisation and cost efficiency.
Familiarity with BI, dashboarding, semantic modelling and analytics engineering practices.
Skills Required
- Bachelor's or Master's in Computer Science, Engineering, Data Science, Mathematics or related, or equivalent experience
- 10+ years hands-on experience in data engineering, building and operating production-grade pipelines and data platforms at scale
- 3+ years people leadership experience including hiring, coaching, mentoring and performance management
- Strong proficiency in SQL
- Strong proficiency in Python
- Experience with distributed data processing frameworks such as Spark or PySpark
- Deep expertise in data warehousing, lakehouse architectures, data modelling and ETL/ELT design
- Experience with cloud data platforms and services such as AWS, Snowflake or Databricks
- Experience with orchestration, transformation and streaming technologies such as Apache Airflow, dbt, Kafka or Kinesis
- Solid understanding of data governance, metadata management, data cataloguing, privacy, security, data quality and observability
- Experience enabling analytics and AI/ML use cases through reliable data products and feature engineering workflows
- Excellent problem-solving, communication and stakeholder management skills
- Experience working in globally distributed engineering organizations
- Hands-on experience with data mesh, feature stores, real-time analytics platforms or modern lakehouse architectures
- Familiarity with infrastructure-as-code, containerization and platform engineering (Terraform, CloudFormation, Docker, Kubernetes)
- Experience managing cloud infrastructure usage, platform reliability, performance optimization and cost efficiency
- Familiarity with BI, dashboarding, semantic modelling and analytics engineering practices
Nike Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Nike and has not been reviewed or approved by Nike.
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Retirement Support — A 401(k) with a company match is complemented by options such as a Mega Backdoor Roth and deferred compensation for eligible earners. Financial coaching and structured savings programs support long-term financial security.
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Equity Value & Accessibility — An Employee Stock Purchase Plan with a stock discount sits alongside broad-based equity vehicles like RSUs and non-qualified stock options. These avenues expand wealth-building opportunities beyond base pay.
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Parental & Family Support — Paid parental leave includes maternity and paternity time, recently expanded in the U.S. to 16 weeks and extended to part-time retail teammates. Additional supports include childcare assistance at select locations and family-building benefits such as fertility, surrogacy, and adoption.
Nike Insights
What We Do
At NIKE, Inc., we innovate to serve athletes*. Every teammate - from coder to creator - plays a role in making these athletes’ dreams real. Our tech, data, and digital teams push limits every day, building the future of sport and the tools that drive it. Here, curiosity is fuel. Innovation is the game plan. Different perspectives keep us on the offense. You’ll solve challenges worth tackling, grow fast and belong to a team that backs you to do the right thing. Bring your drive. Bring your bold. Let’s move the world, together. Take your first step at nike.com/careers * If you have a body, you’re an athlete.
Why Work With Us
At NIKE, Inc., your dedication fuels the future of sport. There is a sense of pride that comes from representing an iconic brand and shaping its future. Here, we treat every day as a new opportunity to push boundaries, ask tough questions and share whole-hearted convictions. We are a team – united by the belief that anything is possible.
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