About the Role
In this key position, you will oversee and develop solutions for our Azure Databricks platform, focusing on data pipeline development, data modelling, and analytics. You'll work on critical internal projects, designing ETL pipelines and creating data models to support digital health business through data-driven insights.
Key Responsibilities include:
1. Building and documenting data pipelines.
2. Automating reconciliations.
3. Improving data capture and flow.
4. Performing deep dive analytics to inform business decisions.
You'll have the opportunity to leverage your data science expertise and communicate findings clearly to stakeholders. Additionally, Key Responsibilities include:
1. Managing competing priorities to deliver project outcomes on time.
2. Building and maintaining strong relationships with stakeholders.
3. Contributing to data design and overall data architecture.
4. Evolution of technologies, platforms, and code to meet business needs.
5. Development and deployment of ETL pipelines for efficient data ingestion and analysis.
6. Automation of data reconciliation and validation processes.
7. Standardization of data extraction queries and implementation of CI/CD pipelines.
Technical Skills:
Proven experience in data engineering, preferably using Azure Databricks is required. Expertise in data warehousing, data modelling, and developing data pipelines is also necessary. Proficiency in SQL and Python, with the ability to analyze transactional datasets and identify gaps in requirements, modelling, and source systems is a must.
What We're Looking For:
A strong data engineer with a passion for creating impactful solutions is sought after. The ability to communicate complex data insights clearly and concisely is essential. A proactive approach to problem-solving and continuous improvement is also expected.