Sr. Data Architect - Data Engineering 3

Ready to turn bold ideas into real-world impact?
At Genpact, we don’t just adapt to change, we lead it. AI and digital innovation are transforming the way businesses work, and we’re at the forefront of it. Genpact’s AI Gigafactory, our industry-first accelerator, exemplifies how we scale advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. Whether tackling complex challenges through large-scale models or agentic AI, our breakthrough solutions tackle companies’ most complex challenges.

If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what’s possible, this is your moment.

Genpact (NYSE: G) is an agentic and advanced technology solutions company. We leverage process intelligence and artificial intelligence to deliver measurable outcomes. With a strong partner ecosystem and decades of client trust, we provide innovative solutions that transform how businesses run. Powered by a team with an active learning mindset and client centricity at its core, we deliver lasting value for the world’s leading enterprises.
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Job Description

Sr. Developer

Job Level: Technical Leadership-T3

Job Description:

Sr. Analytics Developer

The Sr. Analytics Developer is a senior technical individual contributor role focused on designing, building, and optimizing analytics and data solutions for Corporate Tech. This role partners closely with product managers, engineers, architects, and business stakeholders to translate business needs into scalable data models, pipelines andsemantic layers, that improve decision-making across enterprise technology functions. The role is responsible for delivering reliable, governed, and high-performing analytics products while continuously improving engineering standards.

This role emphasizes leveraging modern data platforms such as Azure, Databricks, Azure Data Factory (ADF), and Azure Data Lake Storage (ADLS) to deliver enterprise-grade analytics solutions for Corporate Tech. It includes developing robust data pipelines andsemantic models,; enforcing development standards and governance; and partnering across teams to improve platform reliability, data quality, observability, and operational efficiency.

Operating in a global environment, the role partners with Corporate Tech stakeholders, data platform teams, security, and IT teams to deliver scalable, secure, and governed analytics products that support enterprise priorities.

What will be your key responsibilities

Analytics Solution Development:

• Design, build, and optimize analytics solutions using Azure, Databricks, ADF, and ADLS, ensuring performance, scalability, and maintainability.
• Build and maintain robust data pipelines for ingestion, transformation, and curation of Corporate Tech data.
• Apply engineering best practices across analytics workflows, including testing, deployment, documentation, security, and performance optimization.

Data Products and Stakeholder Delivery:

• Partner with stakeholders to understand business requirements, define metrics, and deliver analytics products that meet user needs.
• Translate complex business processes into scalable data models, reusable datasets, and meaningful KPIs.
• Support prioritization and delivery of analytics enhancements, balancing speed, quality, and long-term sustainability.
• Provide production support for analytics solutions, troubleshooting issues and driving continuous improvement.

Governance and Quality Assurance:

• Implement and follow governance processes for Pull Requests, coding standards, peer reviews, and release management.
• Promote data governance practices including metadata management, documentation, lineage, and data quality controls.
• Ensure analytics solutions align with enterprise architecture, security requirements, and global standards.
• Collaborate with other Azure teams to align on and incorporate Best Practices

Operational Excellence and Support:

• Support deployment and transition of analytics solutions into production with appropriate monitoring and documentation.
• Collaborate with platform and engineering teams to improve reliability, performance, and cost efficiency of analytics workloads.
• Monitor solution health, investigate incidents, and resolve data or reporting issues related to data with minimal business disruption.

Collaboration and Stakeholder Engagement:

• Collaborate closely with engineers, architects, product owners, and business stakeholders to shape scalable analytics solutions.
• Act as a trusted technical partner across regional and global teams, ensuring alignment on requirements, definitions, and delivery approaches.
• Mentor other developers by sharing best practices, reviewing code, and contributing to a culture of continuous improvement.

Continuous Improvement and Innovation:

• Identify opportunities to modernize analytics assets, improve reusability, and streamline data flows across Corporate Tech domains.
• Evaluate and apply advanced analytics techniques, automation, and emerging technologies where they add measurable value.
• Contribute to the evolution of analytics standards, frameworks, and reusable components across the organization.

What are we looking for?

• Technical Expertise:
  • Strong hands-on experience with Azure cloud services (ADF, ADLS, Databricks) and enterprise analytics development.
  • Strong knowledge of SQL, Python, and Spark for data engineering, analytics, and performance optimization.
  • Experience implementing development best practices including version control, testing, CI/CD, and Pull Request governance.
  • Experience with data governance, metadata management, and data quality practices.
• Delivery and Collaboration:
  • Proven ability to partner with cross-functional teams and translate complex requirements into robust analytics solutions.
  • Experience working in agile product or project environments with strong ownership and accountability.
  • Ability to influence technical decisions and mentor peers through hands-on leadership.
• Corporate Tech / Enterprise Analytics Knowledge:
  • Familiarity with enterprise functions such as digital workplace, infrastructure, cybersecurity, finance systems, HR systems, or other Corporate Tech domains is a plus.
  • Experience supporting enterprise platforms and shared services analytics in a global environment is preferred.
• Soft Skills:
  • Strong problem-solving and analytical thinking skills.
  • Excellent communication skills, with the ability to explain technical concepts to technical and non-technical audiences.

Qualifications

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