> Markdown version of [/jobs/ext/3744150-senior-data-engineer-databricks](https://www.wearedevelopers.com/jobs/ext/3744150-senior-data-engineer-databricks). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior Data Engineer - Databricks

- **Company:** Capgemini
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $89,400.0 - $166,398.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Extract Transform Load (ETL), Data Systems, Data Warehousing, DevOps, Python (Programming Language), Performance Tuning, Cloud Services, SQL Databases, Data Streaming, Unstructured Data, Enterprise Software Applications, Snowflake, Apache Spark, Git, Data Lakes, Pyspark, Adserver, Software Version Control, Data Pipelines, Custom Reports, Databricks
- **Published:** October 15, 2026
- **Apply:** https://www.capgemini.com/jobs/574229-en_US_SAPBTP/x/

## About the Role

* 5+ Years of Design and implement ETL/ELT pipelines using Databricks and Apache Spark.
 * Strong proficiency in Python, SQL, and PySpark.
 * 5+ years of Delivery and Project Management experience
 * Knowledge of Delta Lake, datalakehouse concepts, and streaming data.
 * Familiarity with CI/CD pipelines, version control (Git), and DevOps practices.
 * Understanding of data modeling, data warehousing, and performance tuning.
 * Hands-on experience with cloud platforms (AWS, Azure, or GCP).

## Description

Capgemini is hiring a Databricks Data Engineer in NYC. The ideal candidate will lead the design and optimization of scalable data lakehouse solutions while managing end-to-end project delivery, production support, stakeholder relationships, budgets, and service performance. This person will serve as both a technical leader and a trusted client-facing advisor, ensuring high-quality data solutions are delivered efficiently, reliably, and within contractual commitments.

Your role

 * Develop and maintain datalakehouse architectures for structured and unstructured data.
 * Optimize data workflows for performance, scalability, and cost efficiency.
 * Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality data solutions.
 * Monitor and troubleshoot data pipelines, ensuring reliability and accuracy.
 * Integrate Databricks with cloud services (AWS, Azure, or GCP) and other enterprise systems.
 * Oversee daily support operations, resolving client complaints within SLAs, and drive regular cross-platform training to build product and system knowledge across the team.
 * Track support metrics (ticket volume, resolution time, CSAT) and maintain SOPs to keep the team consistent, efficient, and culturally healthy, including regular team rotations.
 * Manage automation/enhancement of supported applications, build ThoughtSpot dashboards and custom reports, and transition new applications into support.
 * Track project costs across GCP and Snowflake, propose cost-saving initiatives, and present monthly cost analyses to clients.
 * Deliver monthly support summaries, proactively flag data issues before they escalate, and coordinate with cross-functional teams (Adserver, Finance, Product, Yield, Cadent, etc.).