Design, build, and maintain scalable data pipelines for real-time and historical data processing.
Set up and optimize databases, data warehouses, and ETL processes to manage large-scale time-series data from sensors (energy consumption, temperature, humidity, occupancy) and external sources (weather, utility data).
Experience in handling and processing large data input volumes (1000s of rows per second)
Collaborate across Product, Customer Success, Installation, and Tech Support to align data architecture with business needs and ensure data quality.
Implement monitoring and logging systems to ensure pipeline reliability and quickly troubleshoot issues.
Work with data scientists to streamline data access, facilitate experimentation, and support predictive model deployment.
Requirements:
Bachelor s or Master s degree in Computer Science, Engineering, or a related field.
3+ years of experience as a Data Engineer, with a proven track record in building and scaling data infrastructure.
Experience managing time-series data is a must.
Expert knowledge in SQL (Postgres), PL/pgSQL, DBT.
Ability to read and optimize query plans
Strong skills in data pipeline and ETL design, with experience in tools like Metaflow, Airflow, and TimescaleDB.
Proficiency in Python, and familiarity with data manipulation frameworks.
Familiarity with data warehousing principles
Strong problem-solving skills and a proactive, fast-learning mindset.