- Design, develop, and maintain enterprise reports, dashboards, and analytical solutions.
- Translate business requirements and reporting needs into effective analytical solutions.
- Develop reporting solutions using Microsoft Power BI and associated technologies.
- Develop reusable reporting datasets and semantic models.
- Define and implement appropriate KPIs, metrics, calculations, and business rules.
- Ensure reports are accurate, performant, user-friendly, and aligned with enterprise reporting standards.
- Support the rationalisation and modernisation of existing reporting solutions as part of the organisation's data platform transformation.
Data Analysis & SQL:
- Analyse complex datasets to identify trends, patterns, anomalies, and business insights.
- Develop complex SQL queries to extract, transform, validate, and analyse data.
- Perform data profiling, reconciliation, and validation across source and target systems.
- Investigate data quality issues and collaborate with Data Engineers to identify and resolve root causes.
- Develop analytical datasets required to support enterprise reporting and decision-making.
- Ensure analytical outputs are based on well-understood and appropriately governed data.
Databricks & Lakehouse Analytics:
- Work with curated data within the organisation's Databricks Lakehouse environment.
- Develop a practical understanding of the Lakehouse architecture and the role of Bronze, Silver, and Gold data layers.
- Consume and analyse data stored in Delta Lake and other supported data formats.
- Collaborate with Data Engineers to define data requirements for reporting and analytics.
- Participate in the migration of legacy reporting solutions onto the modern data platform.
- Help identify opportunities to improve reporting performance, scalability, and data reuse through the Databricks platform.
- Develop an understanding of data lineage and how data flows from source systems through the Lakehouse to enterprise reporting.
- Design and maintain analytical data models suitable for enterprise reporting.
- Apply dimensional modelling principles, including fact and dimension tables.
- Understand and apply concepts such as star schemas, Slowly Changing Dimensions, surrogate keys, measures and dimensions, granularity, hierarchies, and conformed dimensions.
- Work with Data Engineers to ensure reporting datasets are appropriately structured for analytical workloads.
- Contribute to the development of reusable enterprise data models and reporting datasets.
Data Quality, Governance & Controls:
- Perform data validation and reconciliation to ensure reporting accuracy.
- Identify and document data quality issues.
- Work with Data Engineering and other technology teams to resolve data issues.
- Ensure reports and analytical datasets comply with established data governance and reporting standards.
- Maintain clear documentation of business definitions, calculations, data sources, and reporting logic.
- Contribute to enterprise data definitions and KPI standards.
- Support appropriate data access, security, privacy, and governance practices.
- Engage with business stakeholders to understand reporting requirements and analytical needs.
- Facilitate requirements-gathering sessions and translate business requirements into technical and analytical specifications.
- Challenge requirements where appropriate and identify opportunities to improve existing reporting processes.
- Communicate analytical findings clearly to both technical and non-technical stakeholders.
- Support user acceptance testing and obtain stakeholder sign-off on reporting solutions.
- Provide guidance to stakeholders on appropriate use and interpretation of enterprise data.
Reporting Migration & Modernisation:
- Participate in the migration of existing legacy reports and analytical solutions to the modern data platform.
- Assess existing reports to determine business value, usage, dependencies, and migration requirements.
- Identify opportunities to consolidate duplicate reports and datasets.
- Rebuild legacy reporting solutions using modern data and BI capabilities.
- Validate migrated reports against existing production outputs and source systems.
- Support the transition from legacy reporting architectures towards a governed enterprise reporting model.
Desired Skills and Experience:
- 3+ years of experience in data analytics, business intelligence, reporting, or a related analytical role.
- Strong SQL skills, including complex joins, CTEs, window functions, aggregations, subqueries, data transformation, and data validation/reconciliation.
- Strong experience with Microsoft Power BI.
- Experience developing enterprise dashboards and reports.
- Experience developing or consuming Power BI semantic models/datasets.
- Strong understanding of data modelling and dimensional modelling.
- Experience gathering and documenting business and reporting requirements.
- Experience delivering reporting solutions from requirements through to implementation.
- Experience working with large and/or complex datasets.
- Strong data analysis and problem-solving capabilities.
- Experience performing data quality checks and reconciliation.
- Ability to work effectively with Data Engineers, business stakeholders, and technology teams.
- Relevant Azure or Databricks certification
Preferred:
- 3+ years of relevant experience in data analytics, BI, reporting or a related field.
- Experience with Databricks.
- Experience working with Delta Lake.
- Understanding of Lakehouse architecture.
- Experience with Azure-based data platforms and Azure Data Lake Storage.
- Experience with modern data warehousing or cloud data platforms.
- Experience with Python or PySpark for data analysis.
- Familiarity with Git and modern software development practices.
- Experience with enterprise data governance and data lineage.
- Experience migrating legacy reporting platforms to modern BI/data platforms.