Lead Data Engineer at Great Eastern Life Assurance Co Ltd

Cuenca, Azuay, Ecuador -

Full Time

Start Date

Immediate

Expiry Date

10 Oct, 26

Salary

0.0

Posted On

12 Jul, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

ETL Development, Data Modeling, Hadoop, Spark, Hive, Cloud Data Services, AWS, Azure, GCP, Big Data Architecture, Data Governance, Insurance Domain Knowledge, Data Pipeline Design, Problem Solving, Interpersonal Skills, Technical Documentation

Industry

Insurance

Description

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

How To Apply:

Incase you would like to apply to this job directly from the source, please click here

Responsibilities

Design, develop, and maintain scalable ETL pipelines and data models within the Hadoop ecosystem to support business analytics. Collaborate with stakeholders to ensure data quality, reliability, and alignment with organizational data architecture standards.