This role is part of the Nike’s Merchandising Technology team within Consumer Product and Innovation (CP&I) organization, working very closely with the globally distributed Engineering and Product teams. CP&I is advancing business capabilities to support athletes by implementing a multi-year roadmap and facilitating quicker decision-making for business users. This role will roll up to the Director Software Engineering based out of Nike India Tech Centre.
WHO WE ARE LOOKING FORWe are looking for experienced Technology focused and hands on Senior Engineer to join our team in Bengaluru, India.
As a Senior Software Engineer, you will play a key role in ensuring that our data products are robust and capable of supporting our Data Engineering and Business Intelligence initiatives.
We are looking for5+ years building cloud‑native software systems, including data-intensive applications.
Strong full‑stack hands-on expertise in:
Python, Node.js, React
AWS (IAM, networking, storage, compute, serverless, monitoring)
Databricks
Good to have data engineering experience with:
Advanced SQL, data modelling
Apache Spark / PySpark, Airflow (or equivalent orchestrator)
Snowflake
Good to have understanding of modern Lakehouse patterns:
Spark optimization and Delta Lake (ACID, schema evolution, time travel)
Medallion architecture (Bronze/Silver/Gold)
Proven experience with data quality, automated validation/testing, and operational monitoring; Tableau experience for validation/insights is a plus.
Strong engineering fundamentals: CI/CD, Git, secure coding practices, and production readiness.
Excellent communication, collaboration, and mentoring skills; able to drive outcomes in complex, ambiguous environments.
Preferred
Familiarity with ML/GenAI integration into pipelines.
Databricks Data Engineer certification.
WHAT YOU’LL WORK ON
Own and optimize large-scale ETL/ELT and data service pipelines and reusable frameworks.
Collaborate with cross-functional teams to translate business requirements into technical solutions.
Guide junior engineers through code reviews and design discussions.
Monitor data quality, availability, and system performance.
Lead CI/CD implementation and improve workflow automation.
