Ab Initio Data Integration Architect

Capgemini
Birmingham
2 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer, Content Understanding

Senior Data Scientist

Senior Data Scientist

Data Scientist - Marketing

Paid Search Lead

Data Scientist

The Data Management practice within the Insights and Data business unit of Capgemini is a global practice involved on a broad range of business and IT focused topics from Information Strategy, Governance, Master Data Management, Data Architecture, Data Migration and Lifecycle Management. We help our clients build an enterprise class data platform that allows them to move ahead in their journey of big data and insights. Primarily working with leading software vendors like SAP, Informatica, IBM, Oracle et al, the team are first and foremost Consultants, putting client requirements and industry best practice at the heart of delivery.

Your Role

As an ETL Specialist your primary focus would be the technical delivery of migration and integration projects for our clients. Our ETL Specialists work closely with the project and client teams to understand the requirements, analyse source and target data architecture and systems, propose the most effective solution and work with a team of experts to deliver.
We are looking for our ETL Specialists to bring in the knowledge of new age ETL tools that work with Big Data and Cloud Computing environments and who have a broad range of scripting experience with multiple technologies. You will be working within the Data Management, Data Warehousing, Big Data and Analytics practices alongside some of the top experts in the country, on some of the largest and most complex client engagements across a variety of industry sectors. You will be given the opportunity to grow and take on responsibility from day one in a challenging but rewarding and meritocratic environment.

What you’ll do:

  1. Advise clients on how to build and run an effective Data Migration/Integration program, using industry best practices
  2. Analysis of Source and Target systems
  3. Analysis of Data Quality and advise on how to improve areas of concern
  4. Develop solutions using Ab Initio and cloud-based services like AWS, Azure, or Google Cloud for data storage and processing
  5. Design the new Ab Initio platform on Cloud
  6. Modify and migrate Ab Initio graphs on VMs to run on Kubernetes containers
  7. Work with offshore nearshore teams to execute the delivery of the project
  8. Design Ab Initio orchestration for real time graphs restart ability and logging
  9. Develop, set up or improve the ETL frameworks and process
  10. Understand the requirements from a programme perspective
  11. Work closely with the client for crafting the functional and technical solution
  12. Work with functional and technical teams
  13. Plan, coordinate, and supervise all activities related to the project implementation

Your Skills and Experience

Experience with Ab Initio:
• Extensive experience working with Ab Initio Co>OP, GDE, express>It, Metadata hub, Authorisation Gateway software.
• Good understanding of Ab Initio concepts like checkpoints, parallelism, graph dynamic layouts
• Continuous Flows in Ab Initio
• Good knowledge of the Google Cloud Platform offerings, storage options and compute options to design a new Ab Initio platform on Cloud.

Extracting data from data sources:
• Databases
• XML
• Flat files
• Excel
• Queues and Topics

Writing SQL queries, functions, procedures (in any of the following - in order of preference):
• Big Data Platforms
• Oracle
• SQL Server
• ERP Solutions
• AWS, Azure, or Google Cloud

What would be useful is experience in any of the following tools:
• Informatica
• Talend
• DataStage
• Similar

Your Security Clearance

To be successfully appointed to this role, it is a requirement to obtain Security Check (SC) clearance.
To obtain SC clearance, the successful applicant must have resided continuously within the United Kingdom for the last 5 years, along with other criteria and requirements.
Throughout the recruitment process, you will be asked questions about your security clearance eligibility such as, but not limited to, country of residence and nationality.
Some posts are restricted to sole UK Nationals for security reasons; therefore, you may be asked about your citizenship in the application process.

What Does 'Get The Future You Want' Mean To You?

You will be encouraged to have a positive work-life balance. Our hybrid-first way of working means we embed hybrid working in all that we do and make flexible working arrangements the day-to-day reality for our people. All UK employees are eligible to request flexible working arrangements.

You will be empowered to explore, innovate, and progress. You will benefit from Capgemini’s ‘learning for life’ mindset, meaning you will have countless training and development opportunities from think tanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard ManageMentor, Cybersecurity qualifications and much more.

Why You Should Consider Capgemini

Growing clients’ businesses while building a more sustainable, more inclusive future is a tough ask. But when you join Capgemini, you join a thriving company and become part of a diverse collective of free-thinkers, entrepreneurs and industry experts. A powerful source of energy that drives us all to find new ways technology can help us reimagine what’s possible. It’s why, together, we seek out opportunities that will transform the world’s leading businesses. And it’s how you’ll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge and always pushing yourself to do better, you’ll build the skills you want. And you’ll use them to help our clients leverage technology to grow their business and give innovation that human touch the world needs. So, it might not always be easy, but making the world a better place rarely is.

About Capgemini

Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 360,000 team members in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fuelled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. The Group reported 2023 global revenues of €22.5 billion.

When you join Capgemini, you don’t just start a new job. You become part of something bigger.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.