Data Analytics Engineer - BI Specialist.

About the organisation.

A leading global technology and analytics company in the computer software industry, serving clients across financial services, payments and fintech. The organization operates at significant scale, combining deep domain expertise with modern cloud-based data platforms. It fosters a collaborative, innovation-driven culture focused on delivering trusted, data-led insights.

About the role.

This hybrid role focuses on designing and delivering enterprise-grade business intelligence solutions and data analytics pipelines. The Data Analytics Engineer will build scalable data models, high-impact dashboards and automated reporting assets that enable stakeholders to make faster, better-informed decisions. You will work across the full analytics lifecycle, from data engineering on modern lakehouse platforms to visualization, governance and BI platform administration.

What you will do.

• Design, build and maintain interactive dashboards and reports in Tableau Desktop and Tableau Server, following strong UX/UI and data storytelling principles
• Develop and optimize advanced SQL queries and dimensional data models to support reliable analytics at scale
• Build and orchestrate data pipelines using PySpark / Apache Spark, Hadoop/Hive and Databricks (Delta Lake, SQL warehouses)
• Implement cloud data workflows on AWS (S3, IAM, Glue) and schedule jobs using Apache Airflow and Control-M
• Leverage Databricks AI/BI capabilities (Dashboards, Genie), Unity Catalog and Databricks SQL to deliver governed, self-service analytics
• Apply AI-assisted development and explore LangChain / Mosaic AI use cases to accelerate analytics delivery
• Administer Tableau Server and manage CI/CD pipelines and version control (Git) for BI assets
• Collaborate with business stakeholders to translate requirements into clear, actionable analytical solutions

What you bring.

• Strong hands-on experience with Tableau Desktop and Tableau Server, plus Power BI or Looker (or equivalent depth)
• Advanced SQL skills and solid understanding of dimensional data modeling
• Experience with PySpark / Apache Spark, Hadoop/Hive and Databricks (Delta Lake, SQL warehouses)
• Working knowledge of AWS services (S3, IAM, Glue) and workflow orchestration tools such as Apache Airflow or Control-M
• Proficiency with Git/version control and CI/CD practices for analytics assets
• Exposure to front-end and visualization tooling such as Figma, HTML/CSS, JavaScript or the Tableau Extensions API is a plus
• Domain experience in payments, financial services or fintech data is highly desirable
• Strong communication and data storytelling skills with the ability to engage business audiences

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