Senior Manager - Tech data Analyst

Genpact
London
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Digital Data Consultant, Data Engineering, Data Bricks, Part Remote

Digital Data Consultant, Data Engineering, Data Bricks, Part Remote

Performance and Data Analyst (SEND)

Performance and Data Analyst SEND

Junior Data Analyst

Ready to shape the future of work?

At Genpact, we don’t just adapt to change—we drive it. 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 at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies’ most complex challenges.

If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that’s shaping the future, 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 genpact.com and on LinkedIn, X, YouTube, and Facebook.

We are inviting applications for the role of Senior Manager, Tech Data Analyst.

In this role, as a data architecture specialist, you will play a crucial role in managing and optimizing the data infrastructure within complex financial systems. You will be responsible for ensuring seamless data flow and integrity across various financial product types, contributing to the organization's data governance and architecture strategies.

Responsibilities

  • Experience in working on data lineage or data architecture.
  • Experience working on large complex financial system architecture. Experience migrating such systems is ideal.
  • Experience working across different financial product types.
  • Ability to write SQL queries (or KDB).
  • Ability to read various development languages such as Java, C++, Perl, Python.
  • Collaborate with firmwide data governance teams to define lineage metadata requirements.
  • Analyze ERS (equity risk systems)’s inputs and outputs with help from the SM.
  • Work with stakeholders to define and map the end-to-end data flow, including sources, transformations, destinations, and dependencies.
  • Create a proposal for an automated data catalogue solution across ERS systems.
  • Identify issues related to data inconsistencies, lineage discrepancies, or errors in data transformation, and coordinate with dev squads to resolve them.

QualificationsMinimum Qualifications

  • Relevant experience in data lineage or data architecture.
  • Proficiency in SQL or KDB.
  • Expertise in Collibra tool.

Preferred Qualifications/Skills

  • Experience with large financial system architectures and migrations.
  • Familiarity with multiple financial product types.
  • Ability to understand Java, C++, Perl, and Python.

Additional Qualities

  • Be a transformation leader in AI, automation, and digital innovation.
  • Drive impactful change for global enterprises.
  • Accelerate your career with hands-on experience, mentorship, and continuous learning.
  • Join a community of 140,000+ innovative problem-solvers.
  • Work within a values-driven culture emphasizing integrity and inclusion.

Join Genpact and take your career to new heights. Let’s build tomorrow together.

Genpact is an Equal Opportunity Employer and considers all applicants without regard to race, color, religion, sex, age, national origin, or other protected characteristics. We are committed to a respectful and inclusive work environment. Please note that Genpact does not charge fees for job applications, and beware of scams asking for payment or equipment purchases related to employment.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.