Key Roles and Responsibilities

1. Data Acquisition, Cleaning & Storage

• Design, develop, and maintain robust data pipelines (ETL/ELT) from multiple data sources.
• Implement data cleaning, standardisation, deduplication, and enrichment processes.
• Establish and monitor data quality frameworks (completeness, accuracy, timeliness).
• Ensure secure data storage and enforce access controls in line with governance standards.

2. Data Warehouse & Data Modelling

• Design and implement scalable Data Warehouse and/or lakehouse architectures.
• Develop dimensional data models (fact and dimension tables) and curated data marts.
• Maintain comprehensive documentation including data dictionaries, lineage, and pipeline runbooks.
• Optimise data performance and cost efficiency (e.g., indexing, partitioning, query tuning).

3. Pricing Strategy Automation

• Build and maintain pricing analytics frameworks, including pricing structures, discount models, and margin analysis.
• Develop automated pricing recommendations using rule-based and statistical methods (e.g., regression, clustering).
• Implement workflows for approvals, audit trails, and exception handling.
• Monitor and refine pricing performance using key metrics such as margin, revenue, and win rates.

4. Analytics, Reporting & Decision Support

• Develop dashboards and reports for business stakeholders (e.g., margin performance, utilisation, pipeline tracking).
• Translate business requirements into analytical solutions and actionable insights.
• Enable self-service analytics through well-defined semantic layers and standardised KPIs.

5. Stakeholder Collaboration & Data Governance

• Work closely with cross-functional teams to define data requirements and KPIs.
• Establish and enforce data governance practices, including naming conventions and access controls.
• Support analytics roadmap planning and continuous improvement initiatives.

Education and Experience

Minimum Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, Information Systems, or a related field.
• 4–7+ years of experience in data analytics, data engineering, or a related role.
• Proven experience in building and maintaining data pipelines and data warehouse solutions.
• Demonstrated experience in pricing, commercial analytics, or revenue optimisation.

Advantageous

• Postgraduate qualification in a relevant field.
• Experience with experimentation (A/B testing), forecasting, or optimisation techniques.
• Exposure to CRM/ERP systems and master data management (MDM).
• Experience with data observability tools and service-level agreements (SLAs).

Skills and Knowledge

Technical Skills

• Strong proficiency in SQL and data modelling techniques.
• Experience with ETL/ELT tools and modern data platforms (e.g., cloud data warehouses).
• Proficiency in data visualisation tools (e.g., Power BI, Tableau, or similar).
• Familiarity with programming languages such as Python or R for analytics.
• Knowledge of statistical modelling techniques (regression, clustering, forecasting).

Analytical & Business Skills

• Strong analytical thinking and problem-solving ability.
• Ability to translate complex data into clear business insights.
• Understanding of pricing strategies, margin optimisation, and commercial dynamics.

Soft Skills

• Strong communication and stakeholder management skills.
• Ability to work cross-functionally in a fast-paced environment.
• High attention to detail and commitment to data quality and governance.
• Self-driven with the ability to take ownership and deliver end-to-end solutions.

Contact information

Hridhaya