Senior Business Analyst (Data & Analytics)

At hubQuest, we build and scale advanced data and analytics hubs for global organizations. We partner with enterprise clients to design, launch, and evolve core data capabilities, enabling scalable analytics, advanced use cases, and data-driven decision-making across regions.

• 5+ years of experience as a Business Analyst in data platform, data engineering, or analytics foundation initiatives. • Proven experience with enterprise-scale data pipelines and datasets. • Strong collaboration skills with Data Engineers and understanding of technical trade-offs. • Excellent stakeholder management and communication skills. • Experience coordinating work across multiple business and technical stakeholders. • Ability to manage timelines, dependencies, risks, and delivery expectations in complex environments. • Ability to explain complex data, platform, and delivery topics to non-technical audiences. • Hands-on experience with SQL and Excel for data validation and exploration. • Experience working in Agile delivery environments. • Fluent English.

Nice to have:

• Experience in FMCG or similarly complex, data-intensive industries.
• Experience working with multiple markets, regions, OpCos, or distributed stakeholder groups.
• Exposure to cloud-based data platforms such as Azure, AWS, or GCP.
• Understanding of data governance, lineage, and master data concepts.
• Familiarity with data modelling approaches like dimensional, domain-oriented, or canonical models.
• Exposure to Python or data orchestration tools.
• Experience contributing to cross-domain data standardisation initiatives.
• Previous exposure to project management, delivery management, or PM/BA hybrid responsibilities.

• Partner with business and data stakeholders to translate core processes into scalable data requirements for enterprise data pipelines. • Lead the definition of common data concepts, metrics, and logic across markets. • Own requirements for data ingestion, transformation, validation, and exposure. • Support delivery planning by managing timelines, milestones, dependencies, and sequencing of work. • Identify delivery risks, data readiness issues, and stakeholder misalignments. • Collaborate closely with Data Engineers on pipeline logic, data models, and quality rules. • Support prioritization and trade-off decisions related to data availability, quality, latency, and timelines. • Contribute to backlog ownership, sprint planning, and delivery tracking within agile squads. • Work with global stakeholders, local OpCos, and technical teams to ensure alignment on scope, priorities, and risks. • Embed data quality, lineage, and governance considerations into pipeline design. • Perform data exploration and validation using SQL and Excel. • Document data flows, definitions, dependencies, decisions, risks, and delivery assumptions. • Mentor Business and Data Analysts on best practices in analysis, pipeline design, communication, and delivery discipline.

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