Novasoft
Location: Bedford (Hybrid)
Experience:
10+ years Job Type:
Full Time or Contract Job Summary : We are seeking a seasoned Lead Data Engineer to architect and lead end-to-end implementation of modern data solutions in a hybrid cloud environment. This role requires strong expertise in Snowflake , AWS Glue , SQL , Python , Spark , and Big Data concepts . The ideal candidate will be a hands-on technical leader who can manage complex projects, mentor engineering teams, and collaborate cross-functionally to build scalable, secure, and high-performing data platforms. Key Responsibilities: Architect, design, and lead the implementation of robust data pipelines using AWS (Glue, EMR, S3) and Snowflake Translate business needs into technical specifications and scalable solutions Build and maintain optimized, reusable data models for analytics and reporting Lead performance tuning, data quality checks, and governance controls including RBAC and row/column-level security Mentor and guide a team of 810+ engineers, ensuring high delivery standards and adherence to best practices Handle production deployments, release planning, and post-deployment support (L2/L3) Implement CI/CD pipelines , job scheduling, and automation of ingestion and transformation tasks Leverage knowledge of insurance data (claims and loss) to enhance decision-making insights Champion continuous improvement, code refactoring, and operational reliability Must-Have Skills: Hands-on Snowflake experience with strong architectural understanding Expertise in ETL design, data ingestion, CDC, incremental/batch processing , and job orchestration Strong command of SQL, Python, and PySpark Deep understanding of data warehousing principles , query optimization , and data quality frameworks Proficiency in Apache Iceberg , AWS Glue , Aurora , RDS , and other AWS services Experience with RBAC , data masking , profiling , and integrating data from multiple sources Ability to lead technical discussions, manage project timelines, and resolve complex delivery challenges Demonstrated success in end-to-end data platform implementation , including training, documentation, and change management Strong problem-solving aptitude and the ability to independently drive technical initiatives Preferred Experience :
10+ years of experience in data engineering , with proven leadership in project delivery Deep experience in big data ecosystems and cloud-based solutions Background in the insurance industry , especially with claims and loss data Familiarity with Agile practices, Scrum ceremonies, and stakeholder engagement in fast-paced teams
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10+ years Job Type:
Full Time or Contract Job Summary : We are seeking a seasoned Lead Data Engineer to architect and lead end-to-end implementation of modern data solutions in a hybrid cloud environment. This role requires strong expertise in Snowflake , AWS Glue , SQL , Python , Spark , and Big Data concepts . The ideal candidate will be a hands-on technical leader who can manage complex projects, mentor engineering teams, and collaborate cross-functionally to build scalable, secure, and high-performing data platforms. Key Responsibilities: Architect, design, and lead the implementation of robust data pipelines using AWS (Glue, EMR, S3) and Snowflake Translate business needs into technical specifications and scalable solutions Build and maintain optimized, reusable data models for analytics and reporting Lead performance tuning, data quality checks, and governance controls including RBAC and row/column-level security Mentor and guide a team of 810+ engineers, ensuring high delivery standards and adherence to best practices Handle production deployments, release planning, and post-deployment support (L2/L3) Implement CI/CD pipelines , job scheduling, and automation of ingestion and transformation tasks Leverage knowledge of insurance data (claims and loss) to enhance decision-making insights Champion continuous improvement, code refactoring, and operational reliability Must-Have Skills: Hands-on Snowflake experience with strong architectural understanding Expertise in ETL design, data ingestion, CDC, incremental/batch processing , and job orchestration Strong command of SQL, Python, and PySpark Deep understanding of data warehousing principles , query optimization , and data quality frameworks Proficiency in Apache Iceberg , AWS Glue , Aurora , RDS , and other AWS services Experience with RBAC , data masking , profiling , and integrating data from multiple sources Ability to lead technical discussions, manage project timelines, and resolve complex delivery challenges Demonstrated success in end-to-end data platform implementation , including training, documentation, and change management Strong problem-solving aptitude and the ability to independently drive technical initiatives Preferred Experience :
10+ years of experience in data engineering , with proven leadership in project delivery Deep experience in big data ecosystems and cloud-based solutions Background in the insurance industry , especially with claims and loss data Familiarity with Agile practices, Scrum ceremonies, and stakeholder engagement in fast-paced teams
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