Software Engineer- Data Engineering (Staff/ Sr Staff)

Equilibrium Energy is a clean energy startup focused on building an AI operating system for the power sector. They are seeking a Staff/Sr Staff Software Engineer in Data Engineering to lead data architecture design and implementation, supporting energy trading and AI development through scalable data initiatives.

Responsibilities:

• Design and implement the long-term data architecture using modern technologies and frameworks
• Build and maintain scalable ETL/ELT pipelines in Python, SQL, and dbt—ingesting data via APIs, web scraping, and streaming sources
• Develop and operate data pipelines using orchestration frameworks such as Temporal and Dagster
• Design data models and schemas for our cloud warehouse (Databricks) and relational databases; contribute to the development of our ML feature store
• Optimize workflows for performance and cost efficiency
• Drive large, cross-functional data initiatives from planning to execution
• Partner with AI and engineering teams to ensure high-quality datasets for machine learning and analytics
• Collaborate with product managers, scientists, and engineers to gather requirements and deliver robust data products
• Mentor other engineers in best practices for data ingestion, architecture, and scalable pipeline design
• Support the software testing cycle, debug code, and resolve issues found during QA or user acceptance testing

Requirements:

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field
• 7+ years of progressive experience in data or software engineering
• Advanced programming skills in Python and SQL
• Experience building globally distributed data systems and real-time pipelines
• Hands-on with orchestration/stream processing tools like Temporal, Dagster, Airflow, Spark, or Kafka
• Strong knowledge of relational and NoSQL databases (e.g., Postgres, MySQL, MongoDB, ElasticSearch, Cassandra)
• Familiarity with data warehousing and cloud computing (Databricks and AWS preferred)
• Experience mentoring engineers and providing architectural direction
• Strong analytical skills, with the ability to work with unstructured or ambiguous datasets
• Commitment to data quality, testing, and observability
• Experience with both OLTP and OLAP data processing systems
• Experience with energy market data or weather data sources (e.g., NWS, NOAA, Yes Energy)
• Experience using dbt for transformations and data quality checks
• Collaborating with data science teams to build and productionize ML pipelines
• Familiarity with DataOps practices and CI/CD for data workflows
• Knowledge of real-time data technologies, graph databases, or unstructured data processing
• Understanding of power systems, grid operations, or financial aspects of energy trading