About the Role
We 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 Responsibilities
Leadership & Team Management
- Lead 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 & Execution
- Oversee 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 & Collaboration
- Collaborate 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 Management
- Proactively identify project risks, dependencies, and issues; develop and execute mitigation plans.
- Ensure governance, compliance, and alignment with organizational standards and methodologies.
Must-Have Skills
- 12+ 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 Skills
- Experience 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 knowledge
- Knowledge of Data Vault 2.0 and modern data modeling techniques.
About the Role
We 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 Responsibilities
Leadership & Team Management
- Lead 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 & Execution
- Oversee 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 & Collaboration
- Collaborate 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 Management
- Proactively identify project risks, dependencies, and issues; develop and execute mitigation plans.
- Ensure governance, compliance, and alignment with organizational standards and methodologies.
Must-Have Skills
- 12+ 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 Skills
- Experience 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 knowledge
- Knowledge of Data Vault 2.0 and modern data modeling techniques.
Educational Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.