Senior Data Engineer - Databricks

Senior Data EngineerChoosing 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. Job Location This is an onsite role based in NYC, NY. About the Job You're Considering We are seeking a Senior Data Engineer with expertise in Databricks, Apache Spark, and Cloud Data Platforms to lead data engineering initiatives while managing client delivery, support operations, and project execution. Your Role Design, build, and optimize scalable data pipelines and lakehouse solutions. Lead project delivery, resource planning, risk management, and stakeholder communication. Manage support operations, ensuring SLA compliance and high customer satisfaction. Collaborate with business, analytics, and engineering teams to deliver data-driven solutions. Develop dashboards, reports, and automation initiatives to improve operational efficiency. Monitor cloud and platform costs (GCP/Snowflake) and drive cost optimization efforts. Manage client relationships, monthly reviews, escalations, and commercial discussions. Identify process improvements, support new application onboarding, and drive continuous innovation. Skills and Experience 5+ years of hands-on experience designing and developing ETL/ELT pipelines using Databricks, Apache Spark, and PySpark. Strong proficiency in Python, SQL, and PySpark. 5+ years of Project/Delivery Management experience. Experience with Delta Lake, Data Lakehouse architecture, streaming data, and data warehousing. Hands-on experience with AWS, Azure, or GCP. Knowledge of CI/CD, Git, DevOps practices, and performance tuning.