Health Data Platform Engineer: Pipelines, ML & Governance

Neko Health; Stockholms kommun; On-site; SEK 545,197 - 763,275; Full time

Job summary

Neko Health is seeking a Data Engineer to enhance their Data-to-AI platform, pivotal in driving healthcare innovation. You will design and build data systems that ensure strong governance, quality, and compliance.

Your key responsibilities include developing scalable data pipelines, managing data models, and collaborating with teams to enhance data quality. Candidates should possess strong Python and SQL skills and experience with cloud infrastructure.

Qualifications

• Strong programming skills in Python and SQL.
• Hands-on experience with relational and NoSQL databases, data lakes, and lakehouse technologies.
• Experience working with cloud infrastructure (Azure, AWS, or GCP).
• Familiarity with CI/CD pipelines and automated testing practices.
• Strong data quality and observability experience.
• Experience with data governance practices including lineage and data contracts.

Responsibilities

• Build and own scalable data pipelines for data ingestion and processing.
• Architect and maintain robust data models for analytics and ML.
• Develop core data platform components and infrastructure.
• Ensure data integrity and quality through monitoring and traceability.
• Manage and optimize data infrastructure resources.
• Implement metrics and observability using logging and monitoring.
• Troubleshoot production issues and performance bottlenecks.
• Collaborate with data scientists, analysts, and engineers.

Skills

Python programming

SQL

Relational databases

NoSQL databases

Data lakes/lakehouse technologies

Cloud infrastructure

CI/CD pipelines

Data governance practices

Data quality and observability

Job description

Neko Health is seeking a Data Engineer to enhance their Data-to-AI platform, pivotal in driving healthcare innovation. You will design and build data systems that ensure strong governance, quality, and compliance.

Your key responsibilities include developing scalable data pipelines, managing data models, and collaborating with teams to enhance data quality. Candidates should possess strong Python and SQL skills and experience with cloud infrastructure.