Databricks Lead developer

Infosys•Indianapolis, IN

About The Position

Infosys is seeking an Databricks Lead developer with experience in building large data warehouse . In this role, you will interface with key stakeholders and apply your technical proficiency across different stages of the Software Development Life Cycle including Requirements Elicitation, Design, coding and testing. Responsible for architecting and delivering Databricks-based Lakehouse solutions including medallion‑layered Delta Lake pipelines, job orchestration through Databricks Workflows, CI/CD integration using Repos & Azure DevOps, and governance using Unity Catalog. Led optimization initiatives around cluster policies, autoscaling, Photon execution, and data pipeline performance. Partnered with business, platform, and data science teams to enable analytics, BI, and ML workloads on Databricks.

Requirements

Candidates must be located within commuting distance of Indianapolis, IN or Raleigh, NC or Tempe, AZ or Hartford, CT or Richardson, TX or be willing to relocate to the area.
Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
Candidates authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time.
At least 4 years of Information Technology experience
At least 3 years on Databricks
Expertise in PySpark, Spark SQL, Delta Lake, and distributed compute concepts
Strong experience with Azure (preferred) or AWS/GCP ecosystems
Hands on with Databricks Workflows, Repos, Unity Catalog, DBFS, Medallion architecture
Experience with CI/CD, version control, and DevOps for data platforms
Solid understanding of data modelling, warehousing concepts, and performance optimization
Experience leading technical teams and driving end-to-end data solutions

Nice To Haves

Databricks certifications (Data Engineer Associate/Professional, Machine Learning Professional)
Experience with MLflow, feature engineering, or MLOps
Knowledge of data governance and security frameworks
Exposure to Real‑time streaming (Structured Streaming, Kafka, EventHub)
Candidates should be able to build and maintain work relationships with the client leadership team, 3rd party vendors and business partners.
Candidate should involve in effective communications with the offshore delivery team and in conducting & moderating client meetings.
Should have the capacity to bring in additional business by working with client partners by participating in meetings related to business development, technical discussions and new initiatives.

Responsibilities

Architecting and delivering Databricks-based Lakehouse solutions including medallion‑layered Delta Lake pipelines
Job orchestration through Databricks Workflows
CI/CD integration using Repos & Azure DevOps
Governance using Unity Catalog
Led optimization initiatives around cluster policies, autoscaling, Photon execution, and data pipeline performance
Partnered with business, platform, and data science teams to enable analytics, BI, and ML workloads on Databricks
Build and maintain work relationships with the client leadership team, 3rd party vendors and business partners
Involve in effective communications with the offshore delivery team and in conducting & moderating client meetings
Bring in additional business by working with client partners by participating in meetings related to business development, technical discussions and new initiatives