Data Engineer

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)