Senior 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.
• Conduct code reviews and perform rigorous testing to ensure high-quality deliverables.
• 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.
• Architect end-to-end solutions for business analytics product (dashboards or statistical model) from the acquiring of data, contextualizing data for business analytics and integrating of product with business process.
• Act as a business process owner for onboarding users and data products onto the data platform and pipelines supporting dashboards and statistical models.
• 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.
• Monitor data pipelines continuously and collaborate with stakeholders to troubleshoot and optimize performance.

• Bachelor Degree in Computer Engineering, Computer Science, Mathematics, Software Engineering, equivalent fields or proven experience in data engineering
• A minimum 5 years of experience in Business Intelligence / Data Analytics field. An analytics practitioner with proven experience in delivering data-driven business solution and data-driven process augmentation

• Proficiency in tools and platforms such as Hadoop, Spark, Hive, and cloud data services (e.g., AWS, Azure, GCP)
• Hands-on experience with large volumes of data using SQL, Spark, Hadoop, or other big data ecosystems is preferred
• Proven experience in data engineering, ETL development, and big data technologies
• Stakeholder Management – Conversant in Business terms and ability to resolve and explain data analytics issues with Business users and other stakeholders
• A strong team player who is meticulous, detail-oriented, and capable of performing under pressure
• Possesses strong problem-solving and interpersonal skills
• Possesses strong communication skills with the ability to bridge technical and business domains, and proactive problem-solving
• Committed, dependable, and adaptable with the flexibility to support during peak periods and tight deadlines
• Demonstrate high integrity, accountability, and a collaborative mindset
• Takes initiative to improve current state of things and embrace change
• Understanding of banking, insurance and financial services is preferred