Senior Data Engineering Manager at Experian

Nottingham, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

08 May, 26

Salary

0.0

Posted On

07 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Modern Data Architectures, Cloud Technologies, Data Stack Technologies, Technical Leadership, Data Pipelines, Platform Components, Data Mesh Principles, ML Ops Practices, Team Leadership, Data as a Product, Snowflake, Snowplow, Orchestra, AWS Data Services, Data Platform Transformations

Industry

Information Services

Description

Company Description Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to accomplish their financial goals and help them save time and money. We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com. Job Description We are looking for a Senior Data Engineering Manager with expertise in modern data architectures, complex transformations, and large-scale re-platforming. Reporting to the Director of Platform, AI & Data, you will combine technical leadership and the ability to design and deliver scalable, top performance data solutions using contemporary cloud and data stack technologies. You will be hands-on and participate in technical design, architecture reviews, and critical development work with team management. You will lead distributed teams across the UK and India, working with stakeholders across teams to ensure our data strategy aligns with our goals. You'll promote data excellence, foster a culture of ownership and also help inform business strategy through awareness of the evolving technology landscape. This is a hybrid role working in the office 2 days a week. Responsibilities Delivery & Operational Execution Personally contribute to the design and development of critical data pipelines and platform components where complexity or strategic importance demands direct technical input. Balance centralised governance with distributed ownership (Data Mesh principles). Define and track success metrics such as platform adoption, data quality, and stakeholder sentiment. Champion AI-driven productivity practices to enhance engineering and data efficiency and automation and lead implementation of ML Ops practices to support scalable machine learning operations. Leadership & Management Build and lead top performing, inclusive engineering teams across UK and India. Support career development and mentoring within the team. Directly manage individual contributors and foster engineering and data excellence. Champion a culture of treating Data as a Product, embedding standards and accountability across domains. Data Excellence Embed best-in-class data tooling and practices (Snowflake, Snowplow, Orchestra) and optimise data pipelines for reliability and performance. Collaborate with internal platform teams to build internal developer platforms tailored for product engineering teams. Strategic Planning Implement opportunities for data asset reuse and capability sharing across the organisation. Partner with vendors and internal stakeholders to evolve the data ecosystem. Stakeholder & Relationship Management Work with Product, Analytics, Marketing, and Servicing teams to ensure data capabilities meet our needs. Build excellent relationships across ECS and Experian to promote data sharing and collaboration. Be a trusted advisor on data strategy and platform evolution. Qualifications Recent hands-on data engineering experience with AWS data services (Glue, Redshift, SageMaker) or modern OTS data stack tools (Snowplow, Snowflake, Orchestra, dbt, Fivetran or close equivalents). Expertise leading large-scale data platform transformations. Experience scaling and managing distributed teams across geographies. Recent hands-on experience building and optimising data pipelines and platforms, not limited to oversight or governance. Work with cross-functional stakeholders and lead alignment. Additional Information Benefits package includes: Hybrid working - 40% office based Great compensation and discretionary bonus Core benefits include pension, Bupa healthcare, Sharesave scheme and more 25 days annual leave with 8 bank holidays and 3 volunteering days. You can purchase additional annual leave. Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward and recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why. Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity. Grade: C/EB7 #LI-DS1 #LI-Hybrid Experian Careers - Creating a better tomorrow together Find out what its like to work for Experian by clicking here Employee Status: Regular Role Type: Hybrid Department: Technology Schedule: Full Time

Responsibilities

The manager will personally contribute to the design and development of critical data pipelines and platform components while balancing centralized governance with distributed ownership using Data Mesh principles. Responsibilities also include building and leading top-performing, inclusive engineering teams across the UK and India and fostering a culture of treating Data as a Product.