Senior Data Analyst

Senior Data Analyst

Retail Analytics, Data Quality & Delivery

About the Role

Retail analytics, client data intake, data quality, insights and delivery execution Omnistream is looking for a Senior Data Analyst who can operate beyond basic reporting and checklist-based execution. This person will work across client data, retail domain logic, analytics, and product delivery to turn complex business requirements into clear analytical outputs, risks, and recommendations. The role is not a customer service role. It requires someone who can understand the higher-level objective, learn the domain context, break down ambiguous problems, and communicate what needs to be done, why it matters, what the expected outcome is, and what risks or trade-offs need to be managed. 

What You Will Own

● Client data understanding: Work with client and internal teams to understand what data is available, what is missing, what needs to be transformed, and what is required to meet the business objective.

● Analytical problem framing: Break complex retail and supply chain questions into clear analytical tasks, assumptions, outputs, dependencies, and risks.

● Insights and recommendations: Translate data analysis into practical recommendations that product, engineering, and business stakeholders can act on.

● Data quality and reliability: Identify missing values, inconsistent records, incorrect data, duplicates, outliers, and other quality issues that could impact analysis or client delivery.

● Data models and reporting logic: Build and maintain analysis-ready datasets, KPI definitions, dashboards, and recurring reporting outputs.

● Delivery ownership: Manage analytical workstreams, estimate effort, maintain task visibility, assign or coordinate ownership where required, and keep stakeholders aligned on progress and blockers.

● Domain learning: Develop a strong working understanding of retail data, including sales, products, stores, categories, assortment, planograms, promotions, and performance metrics.

Key Responsibilities

● Use SQL and Python to extract, clean, transform, analyse, and validate data from multiple sources.

● Conduct exploratory analysis to identify trends, anomalies, commercial opportunities, and operational risks.

● Create clear data models, dashboards, and analytical outputs that support client deployments and internal decision-making.

● Validate client data for completeness, consistency, reasonableness, and fitness for use by internal and external services.

● Work with engineering teams to ensure analytical requirements are properly translated into data pipeline and platform needs. Omnistream -

● Support client data onboarding by defining data requirements, mapping source data, documenting assumptions, and flagging gaps early.

● Provide technical feedback on proposed analytical approaches, data solutions, and new tools or technologies.

● Document business logic, metric definitions, data transformations, known limitations, and repeatable analytical processes.

● Use project tools such as Jira to track analytical work, dependencies, timelines, ownership, and follow-through.

● Communicate findings clearly to both technical and non-technical stakeholders, including explaining outcomes, limitations, and risks.

• Fluent English communication

What Good Looks Like

● You can take a broad business problem and turn it into a structured analytical plan without needing a detailed checklist.

● You ask the right questions early, especially around data availability, business rules, assumptions, and expected decision outcomes.

● You can identify when data is not fit for purpose and explain the impact clearly rather than forcing the analysis through.

● You are comfortable working in ambiguity and can make sensible progress while dependencies are being clarified.

● You do not just produce reports. You explain what the data means, what action should be considered, and what risks remain.

● You build trust with engineering, product, and business stakeholders by being clear, structured, and commercially practical.