About ValGenesis
ValGenesis is a leading digital validation platform provider for life sciences companies. ValGenesis suite of products are used by 30 of the top 50 global pharmaceutical and biotech companies to achieve digital transformation, total compliance and manufacturing excellence/intelligence across their product lifecycle.

Learn more about working for ValGenesis, the de facto standard for paperless validation in Life Sciences: https://www.valgenesis.com/about

About the Role:

Responsibilities

Architect, Design, develop, and maintain data ingestion, transformation, and orchestration pipelines (batch and real-time)
Build and optimize data Lakehouse architectures using Azure Synapse, Delta Lake, or similar frameworks
Integrate and manage structured and unstructured data sources (SQL/NoSQL, files, documents, IoT streams)
Develop and operationalize ETL/ELT pipelines using Azure Data Factory, Databricks, or Apache Spark
Collaborate with Data Scientists to prepare and serve ML-ready datasets for model training and inference
Implement data quality, lineage, and governance frameworks across pipelines and storage layers
Work with BI tools (Power BI, Superset, Tableau) to enable self-service analytics for business teams
Deploy and maintain data APIs and ML models in production using Azure ML, Kubernetes, and CI/CD pipelines
Ensure scalability, performance, and observability of data workflows through effective monitoring and automation
Collaborate cross-functionally with engineering, product, and business teams to translate insights into action
Mentor junior team members and review their work

Requirements

Experience: 6 to 12 years in Data Engineering or equivalent roles
Programming: Strong in Python, SQL, and at least one compiled language (C#, Java, or Scala)
Databases: Experience with relational (SQL Server, PostgreSQL, MySQL) and NoSQL (MongoDB, Cosmos DB) systems
Data Platforms: Hands-on experience with Azure Data Lake, Databricks
ETL/ELT Tools: Azure Data Factory, Apache Airflow, or dbt
Messaging & Streaming: Kafka, Event Hubs, or Service Bus for real-time data processing
AI/ML Exposure: Familiarity with ML frameworks (TensorFlow, PyTorch) and MLOps concepts
Visualization & Analytics: Power BI, Apache Superset, or Tableau
Cloud & DevOps: Azure, Docker, Kubernetes, GitHub Actions/Azure DevOps
Best Practices: Solid understanding of data modeling, version control, and CI/CD for data systems

Preferred Skills

Preferred Skills (Nice to Have):
Experience in knowledge graph or semantic search solutions
Understanding of LLM-based data retrieval (RAG) patterns
Exposure to data mesh, data fabric, or domain-oriented data architecture
Familiarity with MLflow, Delta Live Tables, or Data Bricks Unity Catalog

Soft Skills

Strong analytical and problem-solving ability
Excellent communication and collaboration skills
Attention to detail and ability to work with large, complex datasets
Creativity and ability to automate repetitive workflows
Passion for continuous learning and innovation in data and AI technologies

We're on a Mission
In 2005, we disrupted the life sciences industry by introducing the world's first digital validation lifecycle management system. ValGenesis VLMS® revolutionized compliance-based corporate validation activities and has remained the industry standard.

Today, we continue to push the boundaries of innovation enhancing and expanding our portfolio beyond validation with an end-to-end digital transformation platform. We combine our purpose-built systems with world-class consulting services to help every facet of GxP meet evolving regulations and quality expectations.

The Team You'll Join
Our customers success is our success. We keep the customer experience centered in our decisions, from product to marketing to sales to services to support. Life sciences companies exist to improve humanity's quality of life, and we honor that mission.

We work together. We communicate openly, support each other without reservation, and never hesitate to wear multiple hats to get the job done.

We think big. Innovation is the heart of ValGenesis. That spirit drives product development as well as personal growth. We never stop aiming upward.

We're in it to win it. We're on a path to becoming the number one intelligent validation platform in the market, and we won't settle for anything less than being a market leader.

How We Work
Our Chennai, Hyderabad and Bangalore offices are onsite, 5 days per week. We believe that in-person interaction and collaboration fosters creativity, and a sense of community, and is critical to our future success as a company.

ValGenesis is an equal-opportunity employer that makes employment decisions on the basis of merit. Our goal is to have the best-qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristics protected by local law.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Lead Software Engineer, Data Engineering