Description :

Summary :

The Data Engineer is a vital role within Modulr and this role will support the continuous improvement and innovation of our data platform, ensuring processes are robust, efficient and scalable.

Specific duties :

- Extract and integrate data from various sources, including APIs, internal databases, and third-party platforms.

- Design and build efficient analytical data models using dimensional modelling methodologies and best practices.

- Build and maintain semantic models to enable self service access to data for internal users.

- Write clean, maintainable, and well-documented code following best practices.

- Write and execute tests and data quality checks.

- Collaborate with cross-functional teams to understand data requirements and develop scalable and effective solutions.

- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery and re-designing infrastructure for greater scalability.

About You :

A successful Data Engineer will have a track-record in delivering results in a fast-moving business and hence be comfortable with change and uncertainty.

Excellent stakeholder management experience is essential to being successful in this role.

- 4+ years of experience in a Data Engineering role.

- Extensive experience with Python and SQL.

- Excellent knowledge of data architecture, data modelling and ETL methodologies.

- Experience using ETL and data orchestration tools.

- Experience integrating with BI tools and building semantic models.

- Proven experience in supporting and working with cross-functional teams in a dynamic environment.

- Comfortable working in fast-paced, agile environments with a focus on getting things done efficiently.

- Understanding of agile methodologies and practices.

Nice to Have :

- Experience using Snowflake.

- Experience using DBT (or similar).

- Experience using semantic layer tools (Cube.dev, AtScale or similar).

- Experience using PowerBI, Streamlit.

- Experience using Data Quality tools (Soda, Great Expectations or similar).

- Building and using CI/CD pipelines.

- Understanding of AI/ML and GenAI frameworks.

- Experience with AWS (if not, then other cloud platforms).