Full Stack Analytics Engineer

Purpose of the job

As a Senior/ BI Analyst - Data Products, you will play a pivotal role in designing, building and delivering enterprise-grade Business Intelligence (BI) data products that enable data-driven decision making across the organization. You will work across the complete analytics lifecycle - from ingesting and transforming data, designing scalable data models and pipelines, to developing intuitive, high-performance BI applications using Tableau and other leading analytics technologies.

This is a hands-on engineering role requiring a blend of Data Engineering, Business Intelligence, Analytics Engineering and Data Product Development. You will collaborate with business stakeholders, product managers, architects and data engineers to translate business requirements into scalable analytical solutions that provide actionable insights.

The ideal candidate is passionate about solving business problems with data, enjoys working across multiple technologies, and thrives in an environment where engineering excellence, performance optimization and user experience are equally important. You will also help shape analytics standards, governance and best practices while continuously improving the organization's BI capabilities.

Key Responsibilities

Data Product Design & Delivery

Design, develop and deliver scalable Business Intelligence data products that provide actionable insights and enable strategic business decision making.

Translate business requirements into robust analytical solutions with measurable business impact.

Data Engineering & Pipeline Development

Build and maintain reliable data ingestion, transformation and orchestration pipelines using SQL, Python and modern ELT/ETL frameworks.

Design efficient data models supporting enterprise reporting, self-service analytics and advanced analytical use cases.

Business Intelligence Development

Design, develop and optimize interactive dashboards, executive scorecards and analytical applications primarily using Tableau, while leveraging other leading BI tools where appropriate.

Create intuitive visualizations that simplify complex business data for technical and non-technical audiences.

Data Modelling & Performance Optimization

Develop dimensional models, semantic layers and analytical datasets that ensure consistency, scalability and high query performance.

Optimize SQL queries, Tableau workbooks, extracts and backend data structures for maximum efficiency.

Analytics & Data Science Enablement

Apply Python for statistical analysis, predictive modelling, automation and advanced analytics.

Collaborate with Data Science teams to operationalize machine learning outputs into production-ready BI products.

Support basic predictive analytics, forecasting and data exploration initiatives.

Cross-Functional Collaboration

Partner closely with Product Managers, Business Analysts, Data Engineers, Architects and Business Stakeholders to priorities requirements and deliver high-quality analytics solutions.

Participate in solution design workshops and provide technical guidance on data product architecture.

Data Governance & Quality

Ensure data accuracy, consistency, lineage and governance across all reporting solutions.

Implement validation, monitoring and quality assurance processes throughout the data lifecycle.

Automation & Innovation

Automate recurring reporting processes, data validation and operational workflows using Python and SQL.

Continuously evaluate emerging BI technologies, AI-assisted analytics capabilities and modern engineering practices to improve productivity and user experience.

Knowledge, skills and experience required

Knowledge, Skills and Experience Required

Our technology stack includes Tableau, SQL, Python, Snowflake, Tableau REST APIs, Git, CI/CD and modern cloud-based analytics platforms.

We're looking for someone who brings:

3–7 years of experience delivering enterprise Business Intelligence and Analytics solutions.

Advanced expertise in Tableau Desktop, Tableau Cloud/Server including dashboard development, performance optimization, security, governance and deployment.

Strong SQL programming skills with experience writing complex queries, stored procedures, performance tuning and analytical data modelling.

Strong Python programming skills for data transformation, automation, API integration and analytical workflows.

Experience designing and building end-to-end ETL/ELT pipelines using modern cloud data platforms.

Solid understanding of dimensional modelling, star schema design and enterprise data warehousing principles.

Experience working with cloud data platforms such as Snowflake, Azure Synapse, Big Query or Amazon Redshift.

Hands-on experience integrating multiple data sources including APIs, relational databases, cloud storage and third-party applications.

Working knowledge of data orchestration tools such as Airflow, dbt or similar workflow automation platforms.

Understanding of version control, CI/CD practices and software engineering principles for analytics development.

Basic understanding of Data Science and Machine Learning concepts including predictive analytics, statistical techniques and model deployment within BI environments.

Strong analytical and problem-solving skills with the ability to translate complex business requirements into scalable technical solutions.

Experience working in Agile delivery environments with cross-functional product teams.

Excellent stakeholder management, communication and presentation skills with the ability to explain technical concepts to both technical and business audiences.

A continuous learning mindset with enthusiasm for emerging technologies including AI-assisted analytics, Generative AI and modern data engineering practices.

A collaborative approach with a passion for building high-quality, scalable and maintainable data products.