Data Systems Engineer
2 days ago
We are seeking a highly skilled Data Systems Engineer to design, develop and govern our data architecture and pipelines. Ideally someone who has worked on multiple projects with large-scale analytical workloads.
The ideal candidate will need to be collaborative, organised, think out-of-the-box and be ready to pursue new opportunities. Most importantly, this role is for an individual who is passionate about making a difference through healthcare.
Key Responsibilities:- Design and implement scalable and robust data architectures for data warehousing and enterprise data platforms.
- Develop and optimize data pipelines and ETL/ELT/CDC (Change Data Capture) workflows using tools such as Fivetran and Cloud Composer.
- Collaborate with data scientists, product managers, and business stakeholders to define data requirements and create logical and physical data models.
- Manage and administer various database systems, including BigQuery, SAP HANA, and PostgreSQL.
- Ensure data quality, integrity, and security across all data platforms and pipelines.
- Work with our AI/ML teams to design data serving layers and feature stores that support Vertex AI workloads.
- Design and develop reporting frameworks and data marts to support business intelligence needs.
- Integrate data platforms with various enterprise systems (CRMs, ERPs) and third-party APIs.
- Define and implement data governance, master data management, and data cataloging strategies.
- Contribute to the full data lifecycle: requirements gathering, architecture, data modeling, development, testing, and deployment.
- Troubleshoot and resolve data platform issues to ensure high availability and optimal performance.
- Document technical designs, data lineage, and architecture for cross-functional reference.
- Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field.
- Proficiency in one or more backend languages/frameworks, with a strong preference for Python or Go.
- Experience with building RESTful APIs and designing microservices for data delivery.
- Solid grasp of data modeling fundamentals, including Kimball and Inmon methodologies.
- Proficiency in writing complex SQL queries and experience with SQL and NoSQL databases.
- Familiarity with data warehousing concepts and best practices, including CDC.
- Strong version-control habits (Git) and experience with CI/CD pipelines.
- Excellent problem-solving, communication, and collaboration skills.
- PASSION FOR CONTINUOUS LEARNING AND ADAPTING TO EMERGING DATA TECHNOLOGIES.
- Hands-on experience designing and deploying production-grade data warehouses.
- Deep experience with Google Cloud Platform (GCP):
- BigQuery for large-scale analytical workloads.
- Cloud Composer for orchestrating complex data pipelines.
- Vertex AI for AI/ML model serving and feature stores.
- Experience with other cloud providers (AWS, Azure) and their data services.
- Working knowledge of data governance frameworks, master data management, and data cataloging tools.
- Experience with data ingestion tools like Fivetran.
- Business-intelligence expertise in building dashboards and reports with Power BI or Tableau.
- Familiarity with other data technologies such as SAP HANA.
- Understanding of MLOps concepts and their application to data pipelines.
- Contributions to open-source data projects or technical blogging/presentation.
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