Data Analyst - Enterprise Reporting & Analytics

Management Level

Job Description & Summary

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Respond effectively to the diverse perspectives, needs, and feelings of others.

• Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.

• Use critical thinking to break down complex concepts.

• Understand the broader objectives of your project or role and how your work fits into the overall strategy.

• Develop a deeper understanding of the business context and how it is changing.

• Use reflection to develop self awareness, enhance strengths and address development areas.

• Interpret data to inform insights and recommendations.

• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.

Key Responsibilities:

Enterprise Reporting & Business Intelligence

• Design, develop, and maintainenterprise 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 identifytrends, 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 identifyand resolve root causes.

• Develop analytical datasets requiredto 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 Golddata 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 identifyopportunities 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.

Data Modelling

• Design and maintainanalytical 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.

• Identifyand document data quality issues.

• Work with Data Engineering and other technology teams to resolve data issues.

• Ensure reports and analytical datasets comply withestablished 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 dataaccess, security, privacy, and governance practices.

Collaboration

• 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 appropriateand identifyopportunities 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 useand 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 determinebusiness value, usage, dependencies, and migration requirements.

• Identifyopportunities to consolidateduplicate 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:

• Essential:

• 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 Microsoft Power BI certification

• 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 PySparkfor 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.

Travel Requirements

Available for Work Visa Sponsorship?

Job Posting End Date