Principal Data Architect

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.

Get to know us at genpact.com and on LinkedIn, YouTube, X, and Facebook.

Responsibilities

The Big Data Principal Data Architect plays a crucial role in designing and implementing high-performing and scalable big data solutions. This role involves leading and overseeing the development of data architecture strategies, ensuring data integrity, and optimizing data management processes for optimal performance. In Roles and

Responsibilities

• 1.
• Develop and implement data architecture strategies to support business goals; 2.
• Lead the design and implementation of big data solutions and data pipelines; 3.
• Collaborate with cross-functional teams to gather requirements and design data models; 4.
• Ensure data quality and integrity through data governance and data management best practices; 5.

• Optimize data storage, processing, and retrieval performance for large-scale data sets; 6.
• Evaluate and recommend emerging technologies and tools for big data processing and analytics; 7.
• Provide technical guidance and mentorship to data engineering teams; 8.
• Stay current with industry trends and best practices in big data technologies and architectures.

Qualifications

Bachelors - Business Analytics, Bachelors - Computer Science, Bachelors - Statistics, Masters - Data Science

Certifications

Certified Data Management Professional - RiversandRiversand, Databricks Certified Associate Developer for Apache Spark 3.0 - Databricks AcademyDatabricks Academy, Databricks Certified Associate Developer for Apache Spark - Databricks AcademyDatabricks Academy, Microsoft Certified: Azure Data Engineer Associate - MicrosoftMicrosoft, Oracle Database 12c Certified Implementation Specialist - OracleOracle

Required Skills

Accounts Payable Process, Accounts Payable Process, Accounts Receivable (AR), Aerospace Manufacturing, Agile Methodology, Automotive Manufacturing, Banking Capital Markets, Change Management, Claims Management, Client Relations, Cloud Computing, Collaboration Tools, Commercial Excellence, Commercial Modeling, Computer Vision, Consumer Electronics, Consumer Packaged Goods (CPG), Databricks Platform, Data Engineering, Design Thinking, Electronic Hardware, Entertainment Journalism, Executive Presence, Healthcare Payors, Inclusion {+ 28 more}

• Language
• English (Required)
• Language Proficiency -
• Proficient - C2
• Additional Job Location -
• Job Type
• Regular
• Master Skill List -
• Data Engineering
• Remote Type -
• Hybrid
• Work Shift -
• Day Job (United States of America)

The approximate annual base compensation range for this position is

• 210,000 to 300,000 USD
• "Los Angeles California-based candidates are not eligible for this role"
• The actual offer, reflecting the total compensation package plus benefits, will be determined by a number of factors which include but are not limited to the applicant's experience, knowledge, skills, and abilities; geographic location; and internal equity.