Data Analyst

Job Purpose

The Data Analyst will work as a member of the data team, leveraging the significant data assets of Relational Data Systems' clients and partners to develop and support reports, information products and data extracts.

The Data Analyst will design, document, and report, information product and data extracts, based on the significant data assets of Relational Data System' clients. This role will include the execution of initiatives related to the design and introduction of new data products based on the needs of commercial clients, as well as initiatives related to reporting and efficiencies for internal stakeholders.

Working as a members of the data team and reporting to the Data Lead, the Data Analyst will work following internal quality processes and industry best practices for ensuring the quality of outcomes, and the security of all relevant data assets.

Key Responsibilities

• Engages with stakeholders to understand the business requirements and assists in specifying possible solutions.
• Analyses existing enterprise data sets and source systems to determine most appropriate data sources to feed the solution, any data gaps, and quality of data sets.
• Influences stakeholders on what could be future-state opportunities, using current data sets.
• Meets current reporting requirements with existing technology, and also delivering more strategic reporting solutions and suite of reports and dashboards.
• Specifies the mapping, business rules, and transformations required to manage the data into target data models.
• Assists in defining the data checks and reconciliations required to ensure quality of source data.
• Documents business data systems and requirements, so that data solutions can be scaled and replicated.
• Uses a broad network of resources to locate possible data sources
• Oversees data mapping and data integration.
• Improves data quality through data cleansing and data wrangling.
• Collaborates with stakeholders to agree on business processes to contribute to the data warehouse.
• Implements systems to replace manual systems for capturing data

Key Capabilities

• Analytics
  • Appropriately uses exploratory, descriptive, behavioural or predictive analytics or other statistics to provide insights and lateral thinking skills to apply the best possible approach.
  • Is persistent and curious, demonstrating ability to identify and utilise a range of data sources and applies reverse engineering methodology effectively.
• Client Focus
  • Utilises a wide network of relationships internally and externally to ensure reports are professionally written, commercially savvy and targeted to current and potential requirements.
  • Ensures reports are professionally written and content is market orientated and demonstrating commercial savvy.
• Data Management
  • Applies SQL and data modelling skills to complex scenarios; and looks for ways to further use the data.
  • Ability to use complex data sets and being able to sense check the outcomes.
  • Analyses source data to validate requirements and ensure data quality.
• Operational Effectiveness
  • Can foresee issues and takes ownership and follows through and minimizes problems.
  • Reviews work and outcomes to identify ways to improve personal or team outcomes and anticipates the impacts and risks of decisions and actions.