Keely DeWit

Data Engineering Lead Terms: All Capgemini contracts are ongoing with a right to hire after 3 months. Conversion at 90 days is rare and pre-specified by Capgemini, but the right to hire remains in place. Target Pay Rate: $98/hr C2C Location:  Warren, NJ Work schedule details: Onsite Details: As a Tech DE Lead, you will be responsible for leading the technical delivery of data engineering solutions, ensuring alignment with platform and domain architecture. You will drive agile execution, mentor engineering teams, and collaborate with cross-functional stakeholders to deliver high-quality data solutions. Responsibilities: • Lead the end-to-end delivery of data pipelines, transformations, and data integration solutions. • Collaborate with platform and domain leads to ensure technical cohesion and alignment with enterprise architecture. • Define and implement source-to-target mapping, business rules, and data quality standards. • Mentor and coach junior engineers, promoting best practices and continuous learning. • Facilitate agile ceremonies, including sprint planning, daily stand-ups, and retrospectives. • Participate in Data Design Review Boards and contribute to data governance practices. • Adapt and work effectively with team members of various experience levels and backgrounds. • Stay current on emerging technologies and industry trends to inform strategic decisions. • Ensure compliance with data security and privacy regulations. • Collaborate with DevOps teams to automate deployment and monitoring of data solutions. Experience Required: • 12+ years of experience in data engineering and solution delivery. • 5+ years of experience in technical leadership roles. • Proven experience in agile project management and stakeholder engagement. • Expertise in ETL development, cloud data platforms, and integration standards. • Familiarity with insurance data and legacy modernization strategies. • Strong facilitation and communication skills across technical and business teams. • Demonstrated ability to lead and influence cross-functional teams. Technologies: • Cloud Platforms: AWS, Azure, Google Cloud Platform • Data Processing: Apache Spark, Hadoop, Databricks • Databases: SQL Server, MySQL, PostgreSQL, MongoDB, Cassandra • Data Integration: Apache Kafka, Apache NiFi, Talend • Data Visualization: Power BI, Tableau, Looker • DevOps: Docker, Kubernetes, Jenkins, Terraform Functional Skills: • Data Modeling and Design • ETL (Extract, Transform, Load) Processes • Data Warehousing • Data Governance and Compliance • Agile Methodologies • Business Intelligence and Analytics • Stakeholder Management • Technical Leadership and Mentoring