Data Engineer (Databricks)

Onit; Pune District; Presencial; INR 2.400.000 - 3.600.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health coverage for employee and 1st 2

Flexible PTO

Family leave & adoption support

Life & disability insurance

Voluntary benefits

Tax-advantaged accounts

Volunteer day

Descripción de la vacante

Onit is building an AI-driven legal operations platform and seeks a Data Engineer to design and operate Databricks-based data pipelines powering benchmarking capabilities. The role involves ingestion from multiple source systems, entity resolution, data quality, and governance in a multi-tenant environment.

Ideal candidates have 5+ years in data engineering, strong Databricks expertise (PySpark, Spark SQL, Delta Lake), and experience with cloud platforms like AWS.

Formación

• 5+ years in data or analytics engineering building production data pipelines in cloud environments.
• Hands-on Databricks experience: PySpark, Spark SQL, Delta Lake, Workflows/Jobs, Unity Catalog.
• Strong SQL and Python with data modelling and lakehouse/medallion architecture experience.
• Experience deduplicating, linking records, and resolving data quality issues at scale.
• CI/CD for data pipelines and cloud platform experience (AWS preferred).
• Clear communication with data scientists, architects, and product stakeholders.

Responsabilidades

• Design, build, and maintain scalable batch and incremental data pipelines in Databricks.
• Implement canonical data model with Data Architect for consistent figures across product surfaces.
• Develop production pipelines for entity resolution across disparate systems.
• Profile data, implement automated quality checks, and monitor data quality against targets.
• Orchestrate and monitor jobs with Databricks Workflows; optimize Spark performance and cost.
• Apply Unity Catalog governance and multi-tenant data isolation; ensure privacy rules.
• Collaborate with Data Scientist and Engineering to expose curated data to product.

Conocimientos

Databricks PySpark

Spark SQL

Delta Lake

Python

SQL

Data modelling

Entity resolution

Data quality monitoring

Cloud AWS

CI/CD for data pipelines

Herramientas

Unity Catalog

Descripción del empleo

About OnitWe're redefining the future of legal operations through the power of AI. Our cutting-edge platform streamlines enterprise legal management, matter management, spend management and contract lifecycle processes, transforming manual workflows into intelligent, automated solutions.We’re a team of innovators using AI at the core to help legal departments become faster, smarter, and more strategic. As we continue to grow and expand the capabilities of our new AI-centric platform, we’re looking for bold thinkers and builders who are excited to shape the next chapter of legal tech.If you're energized by meaningful work, love solving complex problems, and want to help modernize how legal teams operate, we’d love to meet you.

Position Summary

The Data Engineer builds and operates the Databricks-based data pipelines that power a new customer-facing benchmarking capability in Onit's AI-driven legal operations platform. Integrating data from multiple source systems across enterprise legal management, matter management, and spend management, this role turns inconsistent, duplicated, and incomplete source data into a clean, reconciled, and trustworthy foundation for analytics. Working closely with the Data Architect, Data Scientist, and Product, the Data Engineer delivers reliable ingestion, entity resolution, and data quality measurement at scale, with multi-tenant data isolation and privacy built in.

Key Responsibilities

• Pipeline Development: Design, build, and maintain scalable batch and incremental pipelines in Databricks (PySpark, Spark SQL, Delta Lake) that ingest data from multiple source systems into a medallion (bronze/silver/gold) architecture.
• Data Integration & Modelling: Implement the canonical data model defined with the Data Architect, so figures reconcile consistently across every product surface.
• Entity Resolution: Build production pipelines that resolve duplicate and conflicting records across systems that were never designed to reconcile with one another.
• Data Quality Engineering: Profile source data, implement automated data quality checks and expectations, and build monitoring and reporting so data quality stays continuously visible against defined targets.
• Orchestration & Reliability: Orchestrate and monitor jobs with Databricks Workflows, optimise Spark performance and cost, and troubleshoot pipeline failures.
• Governance & Privacy: Apply Unity Catalog governance, multi-tenant data isolation, and anonymisation and aggregation rules for pooled cross-customer analytics.
• Collaboration: Partner with the Data Scientist to productionise comparability models and data quality metrics, and with Engineering to expose curated data to the product.

Required Skills

• 5+ years in data engineering or analytics engineering, building production data pipelines in a cloud environment.
• Hands-on Databricks experience: PySpark and Spark SQL, Delta Lake, Databricks Workflows/Jobs, and Unity Catalog.
• Strong SQL and Python, with solid data modelling skills (dimensional and/or canonical models) and experience with the lakehouse/medallion architecture.
• Practical experience with deduplication, record linkage, or entity resolution, and with diagnosing and remediating data quality problems at scale.
• Experience implementing automated data quality checks, pipeline monitoring, and Spark performance and cost optimisation.
• Experience with cloud platforms (AWS preferred), Git-based version control, and CI/CD for data pipelines.
• Clear communication with data scientists, architects, and product stakeholders, including flagging data limitations early.
• Working proficiency with AI tools (e.g., Claude, Databricks Assistant, GitHub Copilot) to accelerate pipeline development, debugging, and documentation, with the judgment to validate AI-generated code before production use.

Preferred Qualifications

• Databricks certification (e.g., Data Engineer Associate or Professional).
• Experience with streaming or incremental ingestion (e.g., Auto Loader, Structured Streaming, Delta Live Tables).
• Experience building data for benchmarks, scoring models, or analytics intended for external consumption.
• Experience with anonymisation, aggregation thresholds, or privacy-preserving analytics.
• Background in enterprise B2B SaaS or the legal technology domain.

Benefits & Perks That Support You

• Health Coverage: Employee and immediate family members.
• Time Away: Flexible paid time off and 10 company paid holidays annually.
• Family Support: Exceptional paid leave for birth parents, non-birth parents, and caregivers. Onit also offers surrogacy and adoption reimbursement.
• Income Protection: 100% employer-paid life and disability insurance.
• Additional Coverage Options: Voluntary benefits including hospital indemnity, critical illness, accident.
• Tax-Advantaged Accounts: Flexi, NPS.
• Community Engagement: One paid volunteer day each year to give back to the community.

Our Commitment to Applicants

We know that not everyone will check every box in a job description. At Onit, we value diversity, inclusion, and authenticity. If you’re excited about this role but your experience doesn’t align perfectly with every qualification, we encourage you to apply. You may be exactly who we’re looking for.

Onit Values Customer First - Customer success is our success. We deliver value, listen, and act on customer needs. Purposeful Innovation - Innovation fuels our growth. We harness creativity to solve problems and lead with the intentions and expertise. Win as One - Teamwork is how we win. We are accountable, act with integrity, and communicate openly. Intentional Growth - Our people are the difference. We create an environment with compelling work, impactful contributions, and career growth.