WINT Water Intelligence is dedicated to helping businesses reduce their environmental footprint by preventing the hazards, costs, waste, and environmental impact associated with water leaks and waste. Utilizing the power of artificial intelligence and IoT technology, WINT provides a solution for commercial facilities, construction sites and industrial manufacturers looking to cut water waste, reduce carbon emissions and eliminate the impact of water-leak disasters. WINT has been recognized by Fast Company and CB Insights as one of the world’s most innovative AI companies and has won multiple awards including “Next Big things in Tech” and Insurance Times’ claims prevention technology award. 

Job brief

As the Senior Data Engineer, you will own Wint’s data platform and be the main point of contact responsible for its strategy and execution. Your role will encompass architecting data platforms, building efficient pipelines, and ensuring the platform's performance, reliability, and scalability. You will play a key part in supporting Wint’s mission to drive sustainability in water management.

Key Responsibilities

Ownership & Strategy:
Take full ownership of Wint’s data platform, including strategy, architecture, and continuous evolution, ensuring it aligns with the company’s broader goals.

ETL Pipelines:
Design, implement, and maintain efficient ETL workflows for cleaning, transforming, and aggregating large-scale IoT data using modern pipeline tools and cloud-based systems.

Pipeline Maintenance & Monitoring:
Continuously monitor and maintain data pipelines and systems to ensure high performance, reliability, and data integrity.

Collaboration:
Work closely with data scientists, BI-developers, developers, and analysts to understand data needs, translating them into scalable and reliable solutions that fit within a modern architecture.

Data Quality & Integrity:
Implement cutting-edge data validation, cleaning, and transformation techniques to maintain data integrity across modern pipelines.

Performance Optimization:
Optimize cloud-based databases and pipelines for performance, ensuring low-latency access and processing in high-volume, real-time environments.

Required Skills and Experience 

Experience:

• 5+ years of experience as a Data Engineer, with a proven track record of owning and scaling cloud-based data platforms.

Technical Expertise:

• Proficiency in Python and SQL.
• Expertise in modern data architecture, including big data platforms like Airflow, ArgoFlow, Snowflake, Spark, Kafka, and databases like Elasticsearch or Athena.
• Deep knowledge of cloud services, particularly AWS, for building secure, scalable data systems.
• Extensive experience with modern ETL processes, data models, and data warehousing.

Collaboration & Communication:

• Strong ability to collaborate across teams, including data scientists, BI-developers, developers, and analysts.