Delivery Module Lead

Job Description Role: Senior Data Engineer Location: Onsite/USA-NC Who are we looking for? We're seeking an experienced pipeline-centric data engineer to put it to good use in building out ETL and Data Operations framework (Data Preparation / Normalization and Ontological processes). Technical Skills: Lead the development, and maintenance of scalable data pipelines and ETL processes, ensuring data integrity and accessibility for business intelligence and advanced analytics. Manage robust data platforms on the AWS ecosystem, leveraging services like Glue, PySpark, Apache Iceberg, IAM, S3, and Secrets Manager to build a secure and efficient data infrastructure. Provide technical guidance and mentorship to a team of data engineers, fostering a culture of high performance and continuous learning. Utilize deep expertise in various RDBMS (e.g., MySQL, Db2, PostgreSQL, Snowflake) and different data formats (e.g., JSON, Parquet) to drive strategic data initiatives. Champion the adoption of modern data technologies such as Apache Iceberg with AWS Glue to optimize data lake performance and analytics capabilities. Apply advanced proficiency in Generative AI to automate and streamline data analysis, development, and documentation processes. Business Acumen and Stakeholder Communication Translate complex business challenges into clear, data-driven solutions, effectively communicating technical concepts and project progress to both technical and non-technical stakeholders, including senior leadership. Act as a key liaison between the data engineering team and different stakeholders. Experience in insurance domain preferrable AWS Data Engineering certification good to have Key Responsibilities Lead the development of robust data pipelines, using your deep understanding of existing ETL frameworks to build scalable and efficient solutions. Analyze and understand diverse source systems and data formats to create and validate synthetic datasets for testing and development. Ensure Industry best practice is followed in all aspects of project. Leverage generative AI to enhance data analysis, accelerate development, Unit Testing and streamline documentation. Apply statistical analysis to large datasets, uncovering key patterns, identifying potential challenges, and generating actionable insights. Collaborate with business leaders and stakeholders to address the challenges. Qualification: Somebody who has at least 10 plus years of data engineering experience has played a Senior Data Engineer role. Bachelor's degree (or equivalent) in computer science, information technology, engineering, or related discipline Education qualification: Any degree from a reputed college