Databricks Developer

Capgemini•New York, NY

2d•$105,000 - $115,000•Hybrid

About The Position

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Location: Hanover, NJ (3 days/week from office).

Requirements

Experience with Databricks platform.
Proficiency in PySpark, Spark SQL.
Experience with ETL/ELT workflows.
Experience with Delta Lake.
Experience integrating data from multiple sources (databases, APIs, files, streaming).
Experience developing and maintaining Databricks workflows, jobs, and clusters.
Experience implementing Lakehouse architecture and medallion data models.
Experience monitoring and optimizing Databricks workloads.
Experience configuring and managing notebooks, libraries, and automated deployments.
Experience designing and implementing data models for reporting, analytics, and ML.
Experience collaborating with data analysts, data scientists, and business stakeholders.
Experience creating reusable data assets and transformation frameworks.
Experience supporting advanced analytics and AIML use cases.
Experience with cloud platforms (Azure, AWS, or GCP).
Experience integrating Databricks with cloud-native storage and services.
Experience implementing CI/CD practices for data engineering.
Experience ensuring secure and efficient data movement.
Experience implementing data quality checks and validation frameworks.
Experience ensuring compliance with data governance, security, and privacy standards.
Experience supporting metadata management, lineage, and monitoring solutions.
Experience troubleshooting and resolving data processing issues.

Nice To Haves

Experience with Azure, AWS, or GCP.

Responsibilities

Design, develop, and maintain scalable data pipelines using Databricks.
Build and optimize ETL/ELT workflows for batch and real-time data processing.
Develop data solutions using PySpark, Spark SQL, and Databricks notebooks.
Implement Delta Lake solutions to ensure data reliability, performance, and governance.
Integrate data from multiple sources including databases, APIs, files, and streaming platforms.
Develop and maintain Databricks workflows, jobs, and clusters.
Implement Lakehouse architecture and medallion data models (Bronze, Silver, Gold).
Monitor and optimize Databricks workloads for performance and cost efficiency.
Configure and manage notebooks, libraries, and automated deployments.
Design and implement data models to support reporting, analytics, and machine learning initiatives.
Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements.
Create reusable data assets and transformation frameworks.
Support advanced analytics and AIML use cases.
Work with cloud platforms such as Azure, AWS, or GCP.
Integrate Databricks with cloud-native storage and services.
Implement CI/CD practices for data engineering solutions.
Ensure secure and efficient data movement across enterprise systems.
Implement data quality checks and validation frameworks.
Ensure compliance with data governance, security, and privacy standards.
Support metadata management, lineage, and monitoring solutions.
Troubleshoot and resolve data processing issues.

Benefits

Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility

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