Lead Data Engineer

We are seeking a skilled and detail-oriented Data Engineer to design, develop, and maintain robust data pipelines and ETL solutions. This role involves working closely with cross-functional teams to ensure data quality, scalability, and alignment with business and technical requirements.

• Design, develop, test, and maintain scalable ETL pipelines to meet business, technical, and user requirements.
• Collect, refine, and integrate new datasets. Maintain comprehensive documentation and data mappings across multiple systems.
• Create optimized and scalable data models that align with organizational data architecture standards and best practices.
• Drive continuous improvement in data quality through optimization, testing, and solution design reviews.
• Ensure all solutions conform to big data architecture guidelines and long-term roadmap.
• Implement robust monitoring, logging, and alerting systems to ensure pipeline reliability and data accuracy.
• Apply best practices in data engineering to design and build reliable data marts within the Hadoop ecosystem for planning, reporting, and analytics.
• Maintain and optimize data pipelines to ensure data accuracy, integrity, and timeliness.
• Manage code in a centralized repository with clear branching strategies and well-documented commit messages.
• Coordinate with stakeholders to ensure smooth production deployment and adherence to data governance policies.
• Proactively identify and implement improvements to data engineering processes and workflows.
• Develop end-to-end solutions for data modeling in the data warehouse, including data acquisition, contextualization, and integration with business processes.
• Ensure adherence to development standards and perform periodic reviews to maintain pipeline performance and sustainability.
• Coordinate and conduct testing with stakeholders to ensure effective deployment of data pipelines and dashboards.
• Serve as the primary data engineering contact at the stakeholder location, ensuring clear communication and alignment on priorities
• Monitor data pipelines continuously and collaborate with stakeholders to troubleshoot and optimize performance.
• Leverage domain knowledge in insurance to design data models and pipelines that support business processes and analytics.
• Work closely with business stakeholders to understand requirements and translate them into scalable data engineering solutions.

• Diploma with at least 10 years’ working experience, preferably in Life Insurance
• Proven experience in data engineering, ETL development, and big data technologies
• A strong team player who is meticulous, detail-oriented, and capable of performing under pressure
• Proficiency in tools and platforms such as Hadoop, Spark, Hive, and cloud data services (e.g., AWS, Azure, GCP).
• Possesses strong problem-solving and interpersonal skills.
• Committed, dependable, and adaptable with the flexibility to support during peak periods and tight deadlines