Senior Data Analyst

Work across a variety of industries and projects, acting as the bridge between business stakeholders and data engineering teams to translate business needs into scalable data solutions.

About Endava

At Endava, we’re committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectives—because we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know.

Technology is our how.

And people are our why.

For over two decades, we have been harnessing technology to drive meaningful change.

By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses.

From prototype to real-world impact - be part of a global shift by doing work that matters.

Responsibilities

• Lead Data Discovery activities to understand business objectives, processes, and data requirements.
• Elicit, analyze, document, and manage business, functional, non-functional, and data requirements.
• Assess data sources and existing data architectures, identifying opportunities for improvement and optimization.
• Perform data profiling and data quality assessments, identifying issues and proposing remediation actions.
• Design conceptual and logical data models and document data lineage, data dictionaries, and source-to-target mappings.
• Define requirements for data ingestion, transformation, validation, and ETL/ELT processes.
• Translate business needs into clear functional specifications, business rules, and acceptance criteria.
• Ensure end-to-end requirements traceability throughout the project lifecycle.
• Act as the liaison between business stakeholders and technical teams, ensuring successful delivery of data and analytics solutions.
• Collaborate within Agile teams, supporting backlog refinement, sprint planning, and solution validation activities.

Requirements

• Experience gathering, analyzing, and documenting business and data requirements, including gap and impact analysis.
• Experience analyzing datasets, identifying data quality issues, validating information, and investigating discrepancies.
• Good understanding of relational and dimensional data modelling, including entities, relationships, fact and dimension tables.
• Good SQL knowledge, including joins, aggregations, subqueries, and basic window functions.
• Familiarity with data warehouses, data lakes, Lakehouse, and basic ETL/ELT concepts.
• Understanding of how data moves between systems, including data mapping, transformations, and basic API concepts.
• Basic understanding of data lineage, metadata, data ownership, and data protection principles.
• Experience with Power BI, Tableau, or similar reporting tools, including KPI definitions and dashboard development.
• Experience working in Agile teams and collaborating with business stakeholders, Product Owners, Developers, and Data Engineers.
• Ability to investigate issues, communicate findings, clarify requirements, and work independently.
• Excellent written and verbal communication skills in English, with the ability to communicate effectively with technical teams and business stakeholders.

Preferred

• Cloud experience : AWS , Azure, data platforms: Snowflake, Databricks.
• Basic Python knowledge for data analysis.
• Familiarity with AI-assisted analytical tools.
• Exposure to data migration or data transformation projects.
• Our data team has expertise across engineering, analysis, architecture, modeling, machine learning, artificial intelligence, and data science.
• This discipline is responsible for transforming raw data into actionable insights, building robust data infrastructures, and enabling data-driven decision-making and innovation through advanced analytics and predictive modeling.