As a Data Engineer at Leakmited, you will play a key role in building and maintaining the data foundations that power our AI and data-driven products. You will design, implement, and operate robust data pipelines on AWS and Databricks, ensuring high data quality, observability, and reliability across the entire data lifecycle.

You will work in a strongly cross-functional environment, collaborating closely with software engineers, data scientists, operations, and sales teams. This role is ideal for someone who is curious about business needs, enjoys hands-on development, and wants to build meaningful data systems that directly support operational and product decisions.

Our technical stack: Python, geopandas, unity catalog, databricks, SQL, postgresql/ postgis, DBT, github, github actions, AWS, mlflow, spark, langchain/langgraph/langsmith.

Your Responsibilities

• Design, build, and maintain scalable and reliable data pipelines and ETL processes on AWS and Databricks.

• Ensure strong data quality, observability, and monitoring, enabling fast feedback loops and reliable decision-making.

• Collaborate with development teams to integrate data pipelines into production-grade architectures.

• Work closely with operations and business teams to understand use cases, translate business needs into data solutions and deliver them.

• Support the ingestion and processing of structured, semi-structured, and unstructured data.

• Contribute to the evolution of Leakmited’s data architecture with a focus on robustness, scalability, and maintainability.

• Participate in feedback loops to continuously improve data products based on real-world usage and performance.

Your Profile

• At least 3 years of professional experience as a Data Engineer or in a similar hands-on development role.

• Strong experience designing and developing production-grade data architectures, with a solid software engineering mindset.

• Proven ability to act as a primary hands-on contributor, owning architectures and implementations end to end.

• Experience working with AWS and Databricks for data processing and analytics.

• Strong programming skills in Python and SQL, with good software development fundamentals.

• Practical experience with data quality, observability, and monitoring in production environments.

• Business-oriented mindset: ability to prioritize impact and avoid building “tech for tech’s sake”.

• Comfortable working in cross-functional teams (engineering, operations, sales).

• Curious, pragmatic, and collaborative attitude.

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related technical field is a plus.

Nice to have

• Experience with geospatial (GIS) data and/or time-series data.

• Previous experience in a startup or scale-up environment.

• Exposure to ML / AI workflows and production feedback loops.

1. Pre-screening with the Recruiter: Initial conversation to assess mutual fit and introduce the role.

2. Interview with the Head of Data: Assessment of technical & soft skills and relevant experience for the position.

3. Technical Assessment: Completion of a practical exercise to demonstrate technical abilities.

4. In-person Meeting with the Team: Discussion of technical test results and opportunity to meet the team.

5. Offer Presentation: Presentation of the offer and explanation of next steps.