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Open nowPosted yesterday

Lead Software Engineer

Nike744 open roles

Where
Karnataka, India
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Your applicationOpen nowLead Software EngineerNike · Karnataka, India

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Nike's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

13.5% of postings close within 7 days. Measured by our own scanner across the market. Nike postings stay open a median of 20 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.6%3 days
  3. 13.5%7 days
  4. 21.8%14 days
  5. 36.6%30 days
  6. 58.9%60 days
This job: posted yesterday

Nike median: 20 days open

The posting

Job Description

WHO YOU'LL WORK WITH

You will report to the Senior Engineering and will be the technical leader for one of our data product squads. You will partner closely with Product Managers, Architects, BI Experience leads, and other engineering leads across Nike to define the strategy and roadmap for our consumption and ontology layers. You will mentor SWE I and SWE II engineers, raise the bar on engineering practices, and help our team reduce KLO/TCO while accelerating delivery.

WHO WE ARE LOOKING FOR

We are looking for senior engineers who lead by example — engineers who write excellent code, drive crisp design discussions, and grow the people around them.

  • A minimum of 7–10 years of backend and/or data engineering experience.
  • Deep expertise in at least one of Java, Python, or Scala, and strong fluency in SQL and data modeling.
  • Proven experience designing distributed systems and data products — microservices, REST/GraphQL APIs, event-driven architectures, batch and streaming pipelines.
  • Hands-on experience with Databricks, Spark, Delta Lake, Unity Catalog (or equivalent), and orchestration tools such as Airflow.
  • Strong cloud experience (AWS, GCP, or Azure) including networking, IAM, secrets, and cost-aware architecture.
  • Demonstrated ability to lead technical design reviews, define APIs and data contracts, and drive consensus across teams.
  • Track record of mentoring engineers — code reviews, design coaching, career growth conversations.
  • Experience with observability and SRE practices: metrics, tracing, alerting, error budgets, on-call leadership.
  • Comfortable with TDD, modern CI/CD, and the productive use of AI engineering tools (GitHub Copilot, etc.).
  • Strong written and verbal communication — able to influence both engineers and senior business stakeholders.
  • Bachelor's or Master's degree in Computer Science, Information Systems, or related field — or equivalent experience.
  • Preferred: experience with data governance, RLS/ABAC, ontology/semantic layers, dbt, agentic/LLM-powered analytics layers, or large-scale BI platforms.

WHAT YOU'LL WORK ON

As a Lead Software Engineer in Marketplace Data Engineering, you will own the technical direction of a data product squad serving Nike Direct, Wholesale Demand, Inventory, 3PP Demand, Customer Dimensional data, WFM, Clickstream, Member, or Orderbook.

  • You will lead the design of consumption layers, APIs, and pipelines that BI Experience teams build on — establishing patterns, contracts, and quality bars.
  • You will drive aggressive simplification and unification of our data products landscape, reducing KLO/TCO while improving consistency.
  • You will co-create agentic and ontology-driven consumption experiences with BI Experience teams, embedding business context and metric consistency directly into our code and systems.
  • You will own production reliability, scalability, and security for your squad's services — leading incident response, capacity planning, and the operational quality of what you ship.
  • You will mentor and grow the SWE I and SWE II engineers on the squad, raising the technical bar through reviews, pairing, and design coaching.
  • You will partner with the Platform team to adopt and contribute back recommended toolkits, blueprints, and patterns.
  • You will represent the team in cross-org architecture forums and influence the broader Nike data architecture.
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