Senior Data Platform Engineer AWS, Spark
Experian is hiring a Senior Data Platform Engineer AWS, Spark for a remote role open to applicants in United Kingdom. Level rates it ; you can apply on Experian.
Level's read on this job
- On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
- The posting lists this role as remote.
- Tools and skills the posting cites include AWS, Spark and Snowflake.
- Level lists 395 other open roles at Experian.
- The role was posted in the last few days.
AI in this role
Design and maintain AWS-based data pipelines and platform infrastructure for fraud data capabilities.
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.
Internal Grade D/EB8
Experian Credit Services & Verifications are looking for a Senior Data Platform Engineer to provide hands-on technical leadership for a new fraud data capability that will connect fraud-related data assets into Experian's Data Analytics Platform.
You will work closely with the central Data Analytics Platform team, data owners, security, compliance, platform and delivery stakeholders to agree practical implementation approaches, align with established platform patterns, and ensure the team delivers secure, scalable and supportable solutions.
This is a hands-on engineering role suited to someone who can combine strong data engineering depth with cloud platform experience, engineering discipline and team leadership. You will apply effective DevSecOps practices and contribute to technical roadmap discussions where you will make effective use of CI/CD, Infrastructure as Code and cloud-native tooling, and help drive automation and continuous improvement across the engineering lifecycle.
This is a Hybrid, Nottingham based role (40% in the office) reporting to the Director of Engineering.
Key responsibilities
- Design, build, test and maintain AWS-based data pipelines for fraud-related data assets.
- Support ingestion and transformation of data from source platforms such as Snowflake and internal product/data systems.
- Develop new data flows, integrations and automation as additional data assets are onboarded.
- Work with platform, security and data stakeholders to ensure solutions follow agreed security, governance and compliance patterns.
- Contribute to technical design discussions, review proposals, evaluate options, provide estimates and recommend practical solutions.
- Use Infrastructure as Code and Configuration as Code tooling, such as Terraform, Git and CI/CD pipelines, to deliver repeatable solutions.
- Produce clear documentation covering pipelines, data flows, operational procedures and support processes.
- Support junior engineers where appropriate and contribute to a collaborative, quality-focused engineering culture.
- Use modern engineering practices, including automation and AI-assisted development where appropriate, to improve delivery speed, quality and repeatability.
- Strong experience building data pipelines, data lake solutions or data platform capabilities.
- Strong experience with AWS cloud services relevant to data engineering and platform delivery, including services such as AWS Glue, S3, Step Functions, IAM, Lake Formation, EC2, Lambda, EventBridge and SQS.
- Strong experience with DevOps and Infrastructure as Code tooling, including Terraform, CI/CD pipelines, Git and Jenkins.
- Strong experience developing on Apache Spark or Hadoop.
- Significant programming experience using Scala or Python.
- Strong understanding of cloud security, data privacy, access control and governance principles in data platform environments
Desired skills
- AWS Developer Certification or other relevant AWS certification.
- Strong expertise in Terraform or CloudFormation.
- Experience with OpenShift or Kubernetes.
- Experience with automated testing tools such as pytest or Scalatest.
- Knowledge of RESTful APIs and microservice architectures.
- Experience working with sensitive, governed or regulated data environments.
- Familiarity with data catalogue, metadata management, data marketplace or federated data mesh concepts.
- Great compensation package and discretionary bonus plan
- 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.
Recruitment Fraud Awareness - Experian's recruitment process is conducted only through authorised channels. Recruitment communications will only be sent from an @experian.com email address. Experian will never ask candidates to make any payment as part of an application, interview, assessment, onboarding, or recruitment process. To apply for roles or verify opportunities, please visit experian.com/careers.
Our uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose driven culture is multi award-winning; World's Best Workplaces™ 2025 (Fortune Global Top 25), Great Place To Work™ in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why. Experian is also proud to be an Equal Opportunity and Affirmative Action employer. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.
Experian Careers - Creating a better tomorrow together
Find out what its like to work for Experian by clicking here
How we rate this
Senior Data Platform Engineer AWS, Spark at Experian rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where devsecops was part of your work. What did you do?
- Tell me about a project where infrastructure as code was part of your work. What did you do?
- Tell me about a project where ci/cd was part of your work. What did you do?
- Walk me through how you've used AWS in your day-to-day work.
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- List these exact terms on your resume: Data Engineering, Devsecops, Infrastructure As Code, CI/CD, and AWS. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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