Databricks Data Scientist || Indianapolis, Indiana

[birendra kumar]

Job Title: Databricks Data Scientist

Location: Indianapolis, Indiana

Job Description

Role Descriptions: We are seeking a Databricks Data Scientist with strong experience in Databricks Lakehouse, advanced analytics, and Genie (AI/BI) to design, build, and deploy scalable data science and AI solutions. This role will focus on transforming enterprise data into actionable insights using machine learning, natural language analytics, and self-service BI powered by Databricks Genie

Key Responsibilities

Data Science & Machine Learning

• · Design, develop, and deploy machine learning models using Databricks (MLflow, Spark ML, Python).

• · Implement end-to-end ML pipelines (data ingestion → training → deployment → monitoring).

• · Collaborate with data engineers to ensure reliable, high-quality datasets in the Lakehouse.

• Databricks & Lakehouse Architecture

• · Leverage Databricks Lakehouse (Delta Lake, Unity Catalog) for scalable analytics.

• · Optimize Spark jobs for performance and cost efficiency.

• · Apply best practices for data governance, lineage, and security.

• Genie (AI/BI & Natural Language Analytics)

• · Configure and enable Databricks Genie for self-service analytics.

• · Design semantic layers and curated datasets optimized for natural language queries.

• · Partner with business stakeholders to translate questions into Genie-enabled insights.

• Business Enablement & Collaboration

• · Work closely with product owners, analysts, and business leaders to identify high-value use cases.

• · Communicate complex analytical results in a clear, business-friendly manner.

Required Qualifications

• · Bachelor’s  or master’s degree in data science, Computer Science, Statistics, Engineering, or a related field.

• · 4+ years of experience in data science or advanced analytics.

• · Hands-on experience with Databricks and Apache Spark.

• · Strong programming skills in Python (PySpark, Pandas, NumPy, Scikit-learn).

• · Experience building and deploying ML models in production.

• · Solid understanding of SQL and data modeling.

• · Experience with MLflow, model lifecycle management, and experimentation.