Senior Data Engineer

Capgemini•New York, NY
•$133,000 - $150,000•Onsite

About The Position

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.

Requirements

  • 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.

Responsibilities

  • 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.

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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