Design, develop, and maintain scalable data solutions.
Develop and maintain data pipelines and services.
Write clean, maintainable, and well-tested code.
Implement best practices in software development, data governance, and platform observability.
Collaborate with senior engineers and other team members to design and implement data solutions.
Ensure data quality and reliability through testing and validation.
Participate in code reviews and contribute to team knowledge sharing.
Assist in troubleshooting and resolving production issues.
Additional Information
WHO YOU'LL WORK WITH
At Nike, we leverage the power of data and technology to serve athletes* around the world. The Data Foundation team is at the forefront of this mission-building scalable, secure, and intelligent platforms that power decision-making across Nike's global supply chain and planning ecosystem.
WHO WE ARE LOOKING FOR
We are looking for a skilled software engineer with a passion for building and maintaining data solutions. You thrive in a collaborative environment and have a proven track record of delivering reliable software.
Skillset Required
2-4 years of experience in software development, with a strong foundation in distributed systems and data platforms.
Deep expertise with cloud platforms like AWS, Azure, or GCP.
Hands-on experience with Databricks, Snowflake, AWS EMR, AWS RDS, Azure SQL, or GCP Cloud SQL, Apache Spark, Databricks Workflow and Apache Airflow.
Proficiency in programming languages such as Python or SQL.
Strong understanding of Lakehouse architecture, Data Mesh principles, data governance frameworks, and modern data pipelines.
Proven ability to deliver high-impact, API-first services at scale.
Proficiency with tools like Terraform or AWS CloudFormation is critical for managing cloud infrastructure programmatically, ensuring consistency, and enabling automation.
Strong problem-solving and analytical thinking skills.
Excellent communication and collaboration skills.
Good hands on experience in observability and Data quality
Skillset Preferred (Good to Have)
Basic understanding of Machine Learning and Generative AI concepts
Exposure to LLMs (Large Language Models) and their applications (data cataloging, data schematic layer, data enrichment, etc.)
Familiarity with prompt engineering techniques and evaluation
Experience or exposure to AI frameworks/libraries, Agentic AI such as LangChain, OpenAI APIs, or similar
Understanding of RAG (Retrieval-Augmented Generation) patterns and vector databases is a plus
Awareness of AI guardrails, responsible AI, and data privacy considerations
Nike · Karnataka, India