Lead Data Engineer

As a Lead 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.

Your Responsibilities

• Collaborate in horizontal project teams with data scientists, developers and product owners to integrate data pipelines into production‑grade architectures.
• Design, build, and maintain scalable and reliable data pipelines and ETL processes on AWS and Databricks.
• Support the data scientists in performant deployment of machine learning algorithms.
• Participate in feedback loops to continuously improve data products based on real‑world usage and performance.
• Contribute to the evolution of Leakmited’s data architecture with a focus on robustness, scalability, and maintainability.
• Ensure strong data quality, observability, and monitoring, enabling fast feedback loops and reliable decision‑making.
• Work closely with operations and business teams to understand use cases, translate business needs into data solutions and deliver them.

Your Profile

• 3+ years of professional experience as a Lead 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.