Senior Data Engineer, Proximie

• Bachelor’s degree in Computer Science, Mathematics, or related field (or equivalent practical experience)
• Minimum of 5+ years as a Data Engineer with experience developing and supporting with data lakes, warehouses preferably on AWS
• Extensive experience designing, deploying, and maintaining data infrastructure on AWS (or equivalent), including data lakes, warehouses, and real-time pipelines
• Experience across a variety of AWS products such as S3, Glue, EMR, Lambda, Aurora or equivalents
• Professional software development experience with Python and SQL
• Able to work as a team to deliver against requirements in a collaborative and agile way

Desirable

• As Proximie continues its global expansion, we are seeking a Senior Data Engineer to join our data engineering team
• Our data has become more important than ever
• We need to utilise it to make analytical decisions, store it securely, move it between different systems, all the while ensuring that we adhere to healthcare and data protection regulations
• As a Senior Data Engineer you’ll help shape the future of Proximie’s Data & Insights platform, ensuring our systems are robust, secure, and scalable to power analytics, AI, and data products used by hospitals worldwide
• Reporting to a Data Engineering Lead based in the UK, the Senior Data Engineer will be responsible for:
• Design, evolve and future-proof scalable data architectures to meet performance, cost, and reliability goals
• Build and orchestrate resilient batch and real-time data pipelines
• Data modelling & cataloguing including
• Performance Tuning in various technologies (e.g. Spark, Presto, Athena, Postgres)
• Build automated testing frameworks including implement anomaly detection and validation checks (e.g. with Great Expectations)
• Enforce data access controls, encryption at rest/in transit, PII masking/anonymization, and collaborate on HIPAA/GDPR (or equivalent) compliance
• Manage and version cloud infrastructure using IaC tooling (e.g. Terraform)
• Collaborate closely with Data Scientists, Analysts, Product, and Customer Success teams to design reliable, well-documented datasets and APIs that enable analytics, insights, and ML capabilities
• Drive development of customer-facing data products - APIs, timelines, dashboards - and support machine-learning data pipelines
• Mentor junior engineers, champion best practices, document architectures/runbooks/data dictionaries, and standardize coding conventions and CI/CD