Software Engineer - Data

Onit; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Onit in Pune, India, is seeking a Software Engineer - Data to build and maintain data pipelines, services, and APIs powering analytics across its legal operations platform. This role emphasizes sound software engineering practices and production-grade code.

You will work under Senior Software Engineers and the Data Architect, collaborating with product managers, data scientists, and QA to deliver well-defined features and grow depth in data-intensive systems.

Qualifications

• 3+ years of professional software engineering with data pipelines or data-driven apps.
• Proficiency in Ruby or Python with OOP and clean-code practices.
• Strong SQL and relational DB design (PostgreSQL/SQL Server/MySQL).
• Experience building or consuming REST APIs and data formats (JSON/CSV/Parquet).
• Familiar with ETL/ELT, data validation, and error handling in pipelines.
• Git-based workflows, CI/CD, cloud platforms (AWS), and Docker.
• Ability to review AI-generated code and maintain quality.
• Strong analytical and troubleshooting skills, good communication.

Responsibilities

• Build, test, and maintain data pipelines, backend services, and APIs.
• Write and optimise SQL queries and data models.
• Implement automated tests and data validation checks.
• Investigate, debug, and resolve data and application issues.
• Participate in sprint planning, stand-ups, and code reviews.
• Contribute to technical documentation and knowledge sharing.

Skills

Ruby or Python

SQL

REST APIs

ETL/ELT

Git/CI-CD

AWS

Docker

AI coding tools

Data pipelines

Data quality

Tools

Airflow

Spark

Kubernetes

Parquet

Job description

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.

Key Responsibilities

• 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.

Required Skills

• 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.

Preferred Qualifications

• 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.