Software Engineer - Data

Position Summary

The Software Engineer - Data builds and maintains the data pipelines, services, and APIs that power analytics and AI features across Onit's legal operations platform, spanning enterprise legal management, matter management, spend management, and contract lifecycle management. This engineering-focused role applies sound software engineering practices to data, writing clean, tested, production-grade code. Working under the guidance of Senior Software Engineers and the Data Architect, and alongside product managers, data scientists, and QA, the Software Engineer - Data delivers well-defined features and grows technical depth in data-intensive systems.

• Pipeline & Service Development: Build, test, and maintain data pipelines, backend services, and APIs that ingest, transform, and serve data to product features, following established designs and standards.

• SQL & Data Modelling: Write and optimise SQL queries and implement schema changes and data models defined with senior engineers.

• Data Quality: Implement automated tests and data validation checks, and help monitor pipelines so data issues are caught early.

• Troubleshooting: Investigate, debug, and resolve data and application issues in a timely manner, escalating complex problems appropriately.

• Agile Delivery & Code Reviews: Participate in sprint planning, stand-ups, and retrospectives, and take part in code reviews to improve quality and learn from the team.

• Documentation & Learning: Contribute to technical documentation and knowledge sharing, and continuously build skills in data engineering and software design.

• 3+ years of professional software engineering experience, including hands-on work with data pipelines, backend services, or data-driven applications.

• Proficiency in Ruby (or a comparable language such as Python), with solid understanding of object-oriented programming, testing, and clean code practices.

• Strong SQL skills and understanding of relational database design (e.g., PostgreSQL, SQL Server, or MySQL), including writing efficient queries.

• Experience building or consuming REST APIs and working with common data formats (JSON, CSV, Parquet).

• Familiarity with ETL/ELT concepts, data validation, and error handling in data pipelines.

• Experience with Git-based workflows and CI/CD; familiarity with cloud platforms (AWS preferred) and Docker.

• Working proficiency with AI coding tools (e.g., Claude, Cursor) for code generation, debugging, and testing, with the judgment to review and validate AI-generated code.

• Strong analytical and troubleshooting skills, attention to detail, and good verbal and written communication.

• Exposure to distributed data processing (e.g., Spark) or workflow orchestration tools (e.g., Airflow).

• Exposure to analytical or columnar data stores.

• Background in enterprise B2B SaaS or the legal technology domain.