Software Engineer, Data Engineering

Verse is a company focused on helping organizations manage complex energy portfolios by unifying energy data and operations. They are seeking a Software Engineer specializing in Data Engineering to design, build, and maintain data platform tools and pipelines, ensuring data quality and supporting analytical workflows.

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

Requirements:

• 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
• 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 of managed or hosted data solutions such as Databricks, Snowflake, ClickHouse, Tinybird, etc
• Practical knowledge working with data in formats like Parquet, Avro, Protobuf, time series, text, image, video
• Working closely to support AI/ML-focused teams (knowledge of MLflow and Ray is a big a plus)
• Comfort building internal dashboards and data-focused visualizations