Job Description & How to Apply Below
At Genpact, we don’t just keep up with technology—we set the pace. AI and digital innovation are redefining industries, and we’re leading the charge. Genpact’s AI Gigafactory, our industry-first accelerator, is an example of how we’re scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform m large-scale models to 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 advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions – we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on Linked In, X, You Tube, and Facebook.
Inviting applications for the role of Sr. Data Architect - Data Engineering
!
Sr. Data Architect 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 and semantic 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 standard
s.
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 and semantic models,; enforcing development standards and governance; and partnering across teams to improve platform reliability, data quality, observability, and operational efficien
cy.
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 prioriti
es.
What will be your key responsibili
ties Analytics Solution Developm
- ent:
Design, build, and optimize analytics solutions using Azure, Databricks, ADF, and ADLS, ensuring performance, scalability, and maintainabil
- ity.
Build and maintain robust data pipelines for ingestion, transformation, and curation of Corporate Tech d
- ata.
Apply engineering best practices across analytics workflows, including testing, deployment, documentation, security, and performance optimizat
ion.
Data Products and Stakeholder Deli
- very:
Partner with stakeholders to understand business requirements, define metrics, and deliver analytics products that meet user n
- eeds.
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 sustainabi
- lity.
Provide production support for analytics solutions, troubleshooting issues and driving continuous improve
ment.
Governance and Quality Assu
- rance:
Implement and follow governance processes for Pull Requests, coding standards, peer reviews, and release manag
- ement.
Promote data governance practices including metadata management, documentation, lineage, and data quality con
- trols.
Ensure analytics solutions align with enterprise architecture, security requirements, and global stan
- dards.
Collaborate with other Azure teams to align on and incorporate Best Pra
ctices
Operational Excellence and S
- upport:
Support deployment and transition of analytics solutions into production with appropriate monitoring and documen
- tation.
Collaborate with platform and engineering teams to improve reliability, performance, and cost efficiency of analytics…
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