Data Engineer

About the role

As a Data Engineer you will support senior team members and stakeholders in enhancing regulatory processes through data profiling, analytics, and robust engineering solutions. You will help govern, interpret, and transform data into actionable intelligence.

Key responsibilities

• Participate in a high‑performing SCRUM team to deliver BAU activities and roadmap milestones.
• Interpret business requirements, estimate workloads, prioritize tasks and meet delivery deadlines.
• Design, build and maintain highly performant, cost‑effective, secure data pipelines.
• Support, maintain and upgrade existing data workflows, deployment pipelines and infrastructure throughout the application lifecycle.
• Rotate incident‑management duties, troubleshoot incidents, perform root‑cause analyses and document guides.
• Operate using modern CI/CD practices with automated testing, code reviews and approved releases.
• Proactively remediate operational incidents, project risks and impediments, escalating when necessary.

Required profile

• Minimum four years of Data Engineering experience.
• Bachelor’s degree in a relevant field.
• Experience with Agile Scrum, SDLC and data lifecycle processes.

Required skills

• ETL/ELT packages, pipelines or integrations.
• RDBMS concepts: normalization, data modelling, schemas.
• Object‑oriented programming, design patterns, unit testing, CI/CD, debugging.
• Microsoft BI Stack, SQL Server, Integration Services, Analysis Services, Azure Data Factory, Databricks, DevOps.
• Java, Python, R, Power Query M, DAX.
• Big Data concepts: structured/unstructured data, streaming, data lake, governance, lineage.
• Accredited Databricks Data Engineer or Azure certification (preferred).
• Knowledge of PowerBI, Tableau and machine‑learning tools (preferred).