Lead Data Engineer

Position: Lead Data EngineerExperience Required: 8 years+Location: Jersey City, NJEmployment Type: Full-TimeNOTE - Must have taken care of team size of Minimum of 8 or more people and sole contributer required for this role.About the RoleWe are seeking a highly skilled Lead Data Engineer to drive end-to-end data engineering initiatives, lead cross-functional teams, and deliver scalable, cloud-based data solutions. The ideal candidate will bring deep technical expertise, strong leadership, and the ability to collaborate effectively with global stakeholders in a fast-paced environment.Key ResponsibilitiesLeadership & Team ManagementLead and mentor a team of onshore and offshore data engineers to ensure high-quality deliverables.Provide technical direction, coaching, and knowledge sharing to foster team growth and capability building.Establish and enforce engineering best practices, coding standards, and reusable frameworks.Champion innovation, continuous learning, and thought leadership within the data engineering function.Project Delivery & ExecutionOversee end-to-end project delivery, ensuring timely, high-quality execution aligned with project objectives.Define high-level solution designs, data architectures, and ETL/ELT frameworks for cloud-based data platforms.Drive development, code reviews, unit testing, and deployment to production environments.Ensure optimal performance, scalability, and reliability across data pipelines and systems.Stakeholder Communication & CollaborationCollaborate with clients, product owners, business leaders, and offshore teams to gather requirements and define technical solutions.Communicate project updates, timelines, risks, and technical concepts effectively to both technical and non-technical stakeholders.Act as the primary point of contact for client technical discussions, solution design workshops, and progress reviews.Risk & Issue ManagementProactively identify project risks, dependencies, and issues; develop and execute mitigation plans.Ensure governance, compliance, and alignment with organizational standards and methodologies.Must-Have Skills9+ years of experience in Data Engineering with proven experience in delivering enterprise-scale projects.Strong expertise in Big Data concepts, distributed systems, and cloud-native architectures.Proficiency in Snowflake, SQL, and a wide range of AWS services (Glue, EMR, S3, Aurora, RDS, Lambda, Step Functions).Hands-on experience with Python, PySpark, and building cloud-based microservices.Strong problem-solving, analytical skills, and end-to-end ownership mindset.Proven ability to work in Agile/Scrum environments with iterative delivery cycles.Exceptional communication, leadership, and stakeholder management skills.Demonstrated capability in leading onshore–offshore teams and coordinating multi-region delivery efforts.Good-to-Have SkillsExperience with DevOps tools (Jenkins, Git, GitHub/GitLab) and CI/CD pipeline implementation.Experience with cloud migration and large-scale modernization projects.Familiarity with the US insurance/reinsurance domain + P&C Insurance knowledgeKnowledge of Data Vault 2.0 and modern data modeling techniques.Educational QualificationsBachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.