Position- Databricks experts for Data scientists
Exp- 8 yrs
Duration- 6 months
AI engineers - anyone who has been working on LLAMA models, learning how to do vector DB integration and building python scripts and capabilities using Postgres and other AI toolsets to build applications and work in a startup workd very fast and deliver new applications.
We are seeking a highly skilled Senior Data Scientist with deep expertise in Databricks to lead and execute end-to-end data science projects. You will design scalable data pipelines, build advanced machine learning models, and optimize workflows using Databricks on Azure/AWS. This role demands strong analytical skills, coding expertise, and experience collaborating with cross-functional teams to deliver impactful business outcomes.
Key Responsibilities:
- Design, develop, and maintain scalable data pipelines and ETL workflows in Databricks (PySpark / SQL / Delta Lake)
- Apply statistical and machine learning techniques to build predictive and prescriptive models
- Implement ML Ops practices using MLflow, AutoML, model registry, and version control
- Collaborate with Data Engineers, Product Managers, and Business Analysts to understand business requirements
- Conduct exploratory data analysis, feature engineering, and model evaluation using large datasets
- Optimize performance of data science workloads using Databricks Runtime, DBX, and Photon
- Monitor deployed models and continuously improve their accuracy and robustness
- Build dashboards and visualizations using Databricks SQL / Power BI / Tableau
- Ensure best practices in code quality, CI/CD, testing, and documentation
- Guide junior team members and contribute to knowledge sharing within the team
Required Skills & Experience:
- 8+ years of experience in Data Science, with at least 3+ years on Databricks platform
- Expert-level proficiency in PySpark, SQL, Python and machine learning frameworks (Scikit-learn, XGBoost, TensorFlow, etc.)
- Hands-on experience with Databricks on Azure or AWS, including Delta Lake, Unity Catalog, and MLflow
- Strong knowledge of data modeling, big data processing, and cloud-native architecture
- Experience deploying ML models into production and managing their lifecycle
- Familiarity with CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins, etc.)
- Experience with structured and unstructured data, streaming data, and time-series analysis
- Excellent problem-solving, communication, and documentation skills
Preferred Qualifications:
- Databricks Certified Data Engineer Associate / Professional or ML Specialist certification
- Experience with data governance, access control, and security best practices on Databricks
- Domain knowledge in [Finance, Healthcare, Retail, etc.] is a plus
- Experience with notebooks orchestration, job clusters, and cost optimization in Databricks
Tools & Technologies:
- Languages: Python, SQL, PySpark, Scala (optional)
- Platforms: Databricks, Azure / AWS, MLflow, Delta Lake
- Visualization: Power BI, Tableau, Databricks SQL
- Version Control / DevOps: Git, Azure DevOps, GitHub Actions
- Data Sources: Azure Data Lake, S3, Snowflake, SQL Server, PostgreSQL
Job Types: Full-time, Contractual / Temporary
Contract length: 12 months
Pay: ₹100,000.00 - ₹110,000.00 per month
Benefits:
- Health insurance
- Work from home
Schedule:
- Day shift
Work Location: Remote
