Senior Data Engineer

Role & responsibilities

We are hiring a Senior Software Engineer (G6) to shape the future of data engineering at Gap Inc. In this role, you will design and deliver high-impact, cloud-native data solutions that power decision-making across our global retail business. You will work hands-on with cutting-edge technologies like Databricks, PySpark, and Azure/GCP cloud platforms, while mentoring peers, driving engineering best practices, and influencing architecture decisions.

This role is ideal for engineers who thrive on solving complex data challenges, collaborating with diverse stakeholders, and continuously pushing the boundaries of scalability, automation, and innovation. As part of GapTechs growing Hyderabad hub, you will play a critical role in building the next generation of data platforms that fuel our iconic brands worldwide.

Responsibilities

Partner with Product Managers and Solution Architects to define technical requirements and translate them into scalable designs.

Design, build, and maintain reliable cloud-based data pipelines integrating multiple business applications.

Collaborate with business stakeholders to capture and fulfill data requirements for analytics and operations.

Guide team members on applying design patterns, coding standards, and code quality metrics.

Conduct peer code reviews and enforce best practices in software engineering.

Drive continuous improvement in coding, testing, and automation practices.

Work in a DevOps environment with CI/CD pipelines, automated releases, and application monitoring.

Perform root cause analysis on data and processes to identify and resolve issues.

Recommend emerging technologies and solutions that improve platform capabilities.

Contribute technical inputs to Statements of Work for external service providers.

Preferred candidate profile

57years of experience in a Data Engineering role.

Graduate degree in Computer Science or equivalent.

Strong analytical thinking, logical reasoning, and problem-solving skills.

Hands-on expertise with cloud-based data engineering platforms:

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Azure: Databricks, PySpark, Data Lake, Unity Catalog, ADF

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Or equivalent GCP stack: BigQuery, Dataflow, Composer, etc.

Proficiency in building scalable, reliable data pipelines across multiple business applications.