Software Engineer, Data Engineering

Location: United States (remote) What is Verse? Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical. Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs. The Role You will be a member of the technical staff designing, building, and maintaining the next generation of data platform tools, pipelines, and orchestration frameworks to support multiple teams and products across a diverse range of data at Verse. This role supports Core Engineering needs within the organization and builds on top of existing engineering foundations focused on data. As a technical leader with advanced data engineering expertise, teammates will look to you to vet proposals, solutions to internal and customer-facing problems, system designs, and drive the implementation of these solutions with highest standards of software-engineering best practices. You will be an integral part of scaling our data platform as the company grows. Key Responsibilities Ensure data quality, contracts and integrity with best practices around access, governance, and federation throughout the data lifecycle Implement, maintain, and promote best practices and hygiene in our dataland code repository for others to follow and emulate Write shared libraries and reusable data tools across a variety of data flows, sources, and sinks Partnering closely with our Data Science and data-heavy internal teams to support various analytical and AI/ML workflows Foster a culture and mindset of well-designed systems, test-driven software, and proactive communication with a high degree of transparency, mutual respect, and consideration for teammates Participate in code reviews, maintain technical documentation, and adhere to best software development practices What We're Looking For (Minimum Qualifications) Advanced software development skills in Python, Rust, Java, Scala, or similar data-oriented language ecosystems Deep understanding of databases, data {lake,ware}house architectures, and data pipeline solutions across heterogeneous data and workloads in cloud-native environments Proficiency in carefully handling large, complex data and processing them (streaming and batch) in both transactional and analytical settings Commitment to delivering high quality software on time or ahead of schedule while adhering to best software development practices Continuous obsession for staying informed on contemporary technologies, tools, libraries, services, frameworks, or breakthroughs that could benefit the team Discipline using generative AI tools in day-to-day work What Will Make You Standout (Preferred Qualifications) Bachelor’s or master's degree in Computer Science, Data Science, or a related field Senior level software development talent and up Proven track record being a technical leader in high-performing data engineering teams Intimate knowledge of scaling “big data” solutions in cloud-based environments Hands on experience deploying and maintaining software such as Hadoop, Spark, Airflow, DBT, Dagster, Temporal, Presto/Trino, Iceberg, AlloyDB, Postgres, HBase, BigQuery, BigTable, Fabric, Hive, RedShift, S3, GCS, etc. Experience building event-driven architectures with streaming tools such as Kafka, NATS, GCP Pub/Sub, Kinesis, Bufstream, Flink, Beam Knowledge ... (truncated, view full listing at source)