Senior Application Engineer

SKILLS

· Minimum 5 years of hands-on experience in data and application support.

· Strong experience and knowledge in Python and SQL.

· Good written and verbal communication skills.

· Agile, fast learner and able to adapt to changes.

Key Responsibilities

Planning and Design

- Work closely with business analysts, stakeholders, users, and technology teams to understand business requirements, user journeys, functional specifications, and data requirements.

- Design, build, test, and maintain scalable data pipelines, data models, and data integration solutions that support business and operational needs.

- Manage system enhancements, bug fixes, production issues, and change requests, ensuring changes are properly assessed, tested, documented, and aligned with business needs.

Development

- Translate functional and data requirements into robust technical designs, ensuring solutions are reliable, maintainable, and aligned with the defined user journeys.

- Source, ingest, transform, and curate data from multiple internal and external systems, ensuring data is fit for downstream consumption and analytics.

- Work closely with business analysts to validate data logic, business rules, data mappings, and transformation requirements.

- Conduct data profiling, reconciliation, testing, and root-cause analysis to ensure data quality, consistency, completeness, and accuracy.

Documentation and governance

- Develop and maintain technical documentation, including data pipeline designs, data flow diagrams, data mappings, data models, interface specifications, and operational runbooks.

- Support data governance and data management initiatives by implementing required controls, standards, and processes within data solutions.

- Ensure data engineering solutions comply with internal technology, security, risk, and data governance standards.

BAU activities

- Perform BAU monitoring, incident investigation, root-cause analysis, remediation, and production support for data platforms and pipelines.

- Monitor pipeline, platform, and system performance, and proactively identify opportunities for optimization, automation, and resilience improvements.