Cloud Data Architect & Engineer (AWS, Healthcare)

Location Type: Remote Employment Type: Full-time

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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 digital 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 realise their financial goals and help them to save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agrifinance, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data and to innovate. A FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 23,300 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.

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Job Description

As an experienced Cloud Data Architect & Engineer with AWS and healthcare data systems, you will report to Experian Health.

Architecture & Strategy

• Design HIPAA-compliant data architectures using AWS-native services such as AWS HealthLake, Redshift, Glue, Lake Formation, and S3.
• Lead the migration of legacy healthcare data systems to AWS.
• Establish data architecture standards aligned with HIPAA, HITECH, and 21st Century Cures Act requirements.

Data Engineering

• Build, secure, scalable ETL/ELT pipelines using AWS Glue, Lambda, Step Functions, and Athena.
• Integrate healthcare data from EHRs, HL7/FHIR APIs, claims, and IoT devices into centralized data lakes.
• Implement real-time data streaming using Amazon Kinesis or MSK (Managed Kafka).
• Ensure data quality, lineage, and governance using AWS Glue Data Catalog and Lake Formation.
• Automate data workflows using Terraform and CI/CD pipelines.

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Qualifications

• Education: Bachelor's degree in Computer Science, Health Informatics, or a related field.
• Experience:
  • 7+ years' experience in data architecture and engineering, with at least 3 years' experience on AWS.
  • 5+ years' knowledge of healthcare data standards (e.g., HL7, FHIR, ICD-10, CPT, LOINC).
  • 5+ years' proficiency in AWS services: S3, Glue, Redshift, Athena, HealthLake, Kinesis, Lambda, IAM, CloudWatch as well as with SQL, Python, and Spark in cloud environments.
  • Experience with HIPAA, HITECH, and healthcare data privacy/security best practices.
  • AWS certifications (e.g., AWS Certified Data Analytics – Specialty, AWS Certified Solutions Architect – Professional).
  • Experience with healthcare analytics platforms (e.g., Epic Caboodle, Cerner HealtheIntent).
  • Familiarity with Amazon SageMaker for healthcare ML use cases.
  • Experience with orchestration tools like Apache Airflow, dbt, or Dagster.

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Additional Information

Benefits/Perks:

• Great compensation package and bonus plan
• Core benefits including medical, dental, vision, and matching 401K
• Flexible work environment, ability to work remote, hybrid or in-office
• Flexible time off including volunteer time off, vacation, sick and 12-paid holidays
• Explore all our exciting benefits here: https://yourexperianbenefits.com/cand-index.html

Experian Culture:

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 & 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.

Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education.