Job Description

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