Senior Data Platform Engineer AWS, Spark

Qualifications

• 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.

Additional Information

• 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.

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Company Description

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

Job Description

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.