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Nike

Lead Software Engineer, ITC

Posted 2 Days Ago
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Remote
Hiring Remotely in Karnataka, IND
Senior level
Remote
Hiring Remotely in Karnataka, IND
Senior level
Lead design and build of scalable data platforms and pipelines (batch and near-real-time). Develop Python-based services and APIs, optimize SQL/analytical workloads, implement CI/CD and infrastructure automation, drive platform modernization, ensure data quality/governance, mentor engineers, and collaborate with product and business stakeholders.
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WHO YOU WILL WORK WITH

You will be a part of the larger Global Technology organization working on Nike’s internal Supply Chain and Planning Technology (SCPT). You will work day-to-day with a team of engineers, the team’s Product Manager and Principal Engineers in the organization on software projects to achieve Nike’s business objectives. You will also engage with other Global Technology functions and teams on organizational and technical goals

WHO WE ARE LOOKING FOR

We are seeking a highly skilled Lead Software Engineer with deep expertise in Data Engineering, Advanced SQL development, Python programming, GenAI Skills and practical DevOps experience. This role will lead the design, development, and optimization of enterprise-scale data platforms, enabling data-driven decision making through reliable, scalable, and high-performance data solutions. The ideal candidate combines strong hands-on engineering capabilities with technical leadership, mentoring, architectural thinking and the ability to collaborate across product, analytics, platform and business teams.

  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field.

  • 8+ years of software engineering experience with significant focus on Data Engineering.

  • Expert-level SQL skills with experience writing and optimizing complex analytical queries.

  • Strong programming expertise in Python.

  • Experience designing and operating large-scale data platforms and pipelines.

  • Hands-on experience with cloud technologies (AWS, Azure, or GCP).

  • Experience with modern data processing frameworks such as Spark, Databricks, EMR, Snowflake, or equivalent.

  • Experience with Kubernetes, Docker, Terraform, or CloudFormation.

  • Exposure to streaming technologies such as Kafka, Kinesis, or Event Hubs.

  • Experience building observability and monitoring solutions.

  • Familiarity with AI/ML data pipelines and GenAI-enabled platforms.

  • Experience leading enterprise-scale platform modernization initiatives.

  • Practical experience with DevOps practices including CI/CD, infrastructure automation, monitoring and deployment pipelines.

  • Strong understanding of distributed systems, scalability, reliability and performance engineering.

  • Excellent communication, stakeholder management and leadership skills.

WHAT YOU’LL WORK ON

Data Engineering & Architecture

  • Design, develop and maintain scalable data pipelines supporting batch and near real-time processing workloads.

  • Build and optimize data ingestion, transformation and data serving frameworks across large-scale data ecosystems.

  • Lead data modelling initiatives, including dimensional, relational and analytical data structures.

  • Ensure high standards of data quality, governance, reliability and operational excellence.

  • Drive modernisation initiatives across data platforms, tooling and engineering practices.

Software Development

  • Develop robust, maintainable and reusable solutions using Python and related frameworks.

  • Build APIs, automation solutions, and platform services supporting enterprise data products.

  • Apply software engineering best practices including design patterns, test automation, code reviews and CI/CD.

SQL & Performance Engineering

  • Write and optimize complex SQL queries, stored procedures, views and analytical workloads.

  • Perform query tuning, execution plan analysis and performance optimization.

  • Design efficient ELT/ETL solutions ensuring scalability and reliability.

DevOps & Platform Engineering

  • Implement CI/CD pipelines for data and application deployments.

  • Automate infrastructure provisioning, monitoring, alerting and operational workflows.

  • Work with containerization and cloud-native technologies to improve deployment efficiency.

  • Support production systems through observability, reliability, and operational best practices.

Leadership & Collaboration

  • Provide technical leadership for a team of software and data engineers.

  • Drive architecture reviews, technical roadmap planning, and engineering excellence initiatives.

  • Mentor engineers and foster a culture of innovation, ownership, and continuous improvement.

  • Partner with business stakeholders, product teams, architects, and cross-functional engineering teams to deliver impactful solutions.

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