Senior Analytics Engineer

About the Role:

The Senior Analytics Engineer will be responsible for designing, developing, and maintaining end-to-end data solutions. This includes building robust data pipelines that extract from source systems into the data warehouse, transforming raw data into well-modeled datasets readily available for business intelligence, and creating interactive and user-friendly data visualizations using Power BI. The role requires close collaboration with cross-functional teams to empower business stakeholders to derive actionable insights and make data-driven decisions across the organization.

Scope of Work and Responsibilities

•Design and develop scalable data pipelines that extract data from various source systems and transform data inside the data warehouse.

•Transform data into data models that adhere to dimensional modelling techniques i.e. Kimball.

•Create visually compelling and informative dashboards and reports using Power BI.

•Collaborate with data analysts and stakeholders to understand data requirements and deliver meaningful insights.

•Ensure data accuracy and integrity through validation and quality checks.

•Design interactive, user-friendly visualizations tailored to different stakeholder needs.

•Participate in Agile development processes including Scrum and Kanban events.

•Prepare high-level and detailed technical designs for data solutions.

•Apply best practices in coding, testing, and deployment including CI/CD pipelines.

•Stay updated with the latest trends in data engineering and visualization and suggest process improvements.

•Perform other relevant tasks as assigned.

Requirements and Qualifications

Educational Requirements:

Graduate of Bachelor of Science in Information Technology, Engineering, Data Science, or other related fields.

Relevant Experience and Other Requirements:

•At least five (5) years of experience in a senior analytics engineering or developer role.g

•At least five (5) years of experience in architecture, design, and development of integrated systems.

•Strong analytical and problem-solving skills.

•Strong understanding of dimensional modelling techniques

•Familiarity with software development lifecycle and project management methodologies.

•Proven experience with relational databases like Oracle, SQL Server, etc.

•Proven experience developing data pipelines using Python, PySpark and SQL.

•Extensive experience with Microsoft 365 applications.

•Familiarity with cloud platforms such as Azure or AWS.

•Experience in Agile methodologies (e.g., Scrum or Kanban).

•Proficiency in Power BI; experience with Tableau and other visualization platform is a plus.

• Experience with building and maintaining ML or AI pipelines is preferred.

• Exposure to end‑to‑end Generative AI and LLM workflows, including chatbot/assistant integration, basic data preparation, model orchestration, and embedding these capabilities into existing data pipelines is preferred.

• Practical experience supporting ML solutions, such as predictive analytics or forecasting models, including deployment, monitoring, and data lifecycle management within modern data architectures, is preferred.

•Experience with Azure DevOps is preferred.

•Experience with Azure Cloud Services and CI/CD pipelines is an advantage.

•Certifications in Secure Coding, Scrum, or DevOps are a plus.S

•Experience working in teams of five or more members.

•Ability to work with senior executives from diverse cultures.

•Excellent oral and written communication skills in English.