Data Analyst/Engineer

  • Anywhere
  • Anywhere

BAE Systems Applied Intelligence

BAE Systems – Applied Intelligence

Role Profile

1. Role Details


Data Analyst

Grade Range



Data Consulting



2. Role Purpose

The Data Analyst is a junior role in the Data Consulting Practice. Data Analysts will be expected to have overlapping skills offered by other roles, which combined with specific unique skills and responsibilities, result in a separate role of its own right.

The Data Analyst role focus in supporting clients, by serving the data driven needs from current data platforms and processes, enabling a deep understanding of these platforms and processes becoming a key role in supporting the transformation driven by the other Data Consulting roles, either from a structural (strategists), technical (architects) or insight (scientists) perspective.

The role splits into two main areas:

  • A Business oriented area, where Data Analysts will be responsible for the handling of the existing business data systems and processes.
  • A Technical oriented area, where Data Analysts will be responsible for running technical data processes and generating the insight created from existing systems and platforms.

Data Analysts may operate independently, supporting the client to operationalize their systems and processes or with (typically) Data Architects and Data Strategists to support key transformational activities, providing a level of depth and insight into the real issues and problems of the systems and processes.

3. Common Role Accountabilities

  • Proficiency in data investigation, manipulation and analysis techniques supporting the pattern finding and presentation of statistical information.
  • Good understanding of database, data storing and data manipulation solutions and techniques, supported by proficient coding / data querying skills.
  • Ability to ascertain the state of data, data systems and data processes across the organisations, enabling the creation or support of data landscaping exercises, and advise and lead on local improvements whenever appropriate.
  • Ability to extract valuable data and information from unstructured / semi structured noise and present it in an intelligible way to the customer(s).
  • Strong consulting skills ethos, understanding different requirement elicitation and interviewing techniques, able to translate “business request” into “technical data speak”.
  • Responsible for creating tailored data visualisations, ranging from scheduled static reports to dynamic data dashboards.
  • Responsible for leading, managing and designing small improvements across the organisation data systems and processes (e.g. new database / schemas; data quality improvement processes; )

The Data Analyst is to be seen as a junior data adviser to a client and is accountable to serve the client current data needs, by operating the client’s systems, platforms and data, advising on specific tactical improvements whenever appropriate and leading its implementation.

4. Grade/Level Specific Accountabilities

Grade: C1 -Data Analyst

  • General understanding of the Data technologies, their purpose and rationale for utilisation – understands key differences between different data systems and is able to make high level system recommendations regarding its use and applicability.
  • Good understanding of database systems, packages and data storing applications, supported by:
    • Good query language coding ability (e.g. SQL).
    • Identify good and bad quality scripting, enabling the definition of query language best practices and standards.
    • Good knowledge of database concepts, able to operate and build object and data modelling techniques and design principles.
    • Good understanding of tools and techniques that enable the movement and the analysis of data characteristics and statistics in a controlled environment, including:
      • Data collection.
      • Data organisation and structuring.
      • Data Quality assessment and improvement.
      • Generation of statistical analysis.
      • Good understanding of data quality as well as general understanding of reasons that may lead to data quality issues and failing, including:
        • Profiling techniques over data sets
        • Use of profiling and Data Quality improvement toolsets
        • Integration of Data Quality improvement techniques with the general data processing.
        • Ability to implement various forms of dashboards and visualisations, including:
          • Static scheduled reports
          • Dynamic Dashboards
          • Consolidation of operational logs and data execution processing
          • Dashboarding tools and technologies (e.g.: Qlikview; Tableau; Splunk; etc.)
          • Understanding of the different data processing tools and capabilities available in the market place.
          • Understands and applies Agile and Waterfall principles to create Proof of Concepts PoC’s, which can be evolved into production applications.
          • Has an understanding of advanced algorithms and patterns (e.g. segmentation; decision trees; linear regression; etc.) and analytical tooling.
          • Average client and consulting skills enabling conducting data driven interviews and direct engagement with client technical staff.
            • Has awareness of User Centric Design (UCD)

            Grade: C2 – Senior Data Analyst

            • Takes on a lead / SME role, owns specific work areas and coaches others when necessary.
            • Operates with several other resources, understanding key strengths and roles carried out by each job family, (e.g. Data Architects, Data Scientists, Delivery Teams, Business Analysts, etc.) and is able to clearly articulate the data state in the organisation, its limitations and recommended steps for remediation.
            • Takes ownership of one or more areas of work including planning, identifying risks and regular reports to the project manager or client.
              • On small engagements, may assume the duties of a technical project manager.
              • Engages with client stakeholders to understand and document the existing data landscape:
                • Key Data systems
                • Key Data processes
                • Key Data entities
                • Key Data sources and their limitations
                • Relevant Data privacy & security guidelines.
                • Able to translate data findings into “customer-speak” and be able to anticipate and answer the “So-What” questions, or in other words, being able to translate the technical data findings into a context aligned to the business, highlighting both impacts and recommended approaches for mitigation.
                • Able to analyse the suitability of existing data systems, processes, sources, and entities and define approaches to address any limitations found, including:
                  • Planning
                  • Designing technical / process data changes
                  • Recommending use of different toolsets
                  • Ability to conduct both technical and business driven interviews around data needs and requirements, and drive the building of new / updates to existing data components from the interview output. In detail the resource is able to:
                    • Consolidate interview outputs.
                    • Agree requirement prioritisation.
                    • Resolve disputing requirements.
                    • Translate business requirements into technical requirements.
                    • Investigates corporate data requirements and applies data analysis, data modelling and quality assurance techniques, to improve the performance or maintainability of the data estate.
                    • Able to perform complex and advanced analysis on data from different sources and varying levels of quality, including:
                      • Capable of performing continuous monitoring and analysis approaches to systems and data across the organisation.
                      • Provide advice to the client on what the results of Analysis mean for their business.
                      • Has a good understanding of available Open Source software and COTS tools enabling the E2E processing of data, and evaluates potential solutions, demonstrating and commissioning selected products in a range of areas, including:
                        • Data Processing
                        • Data Quality Management
                        • Data Profiling
                        • Data Storing
                        • Data Visualisation

                        DiDiversity and Inclusion Commitment

                        BAE Systems is an equal opportunities employer and actively promotes diversity in the workplace, believing that securing the best people involves being flexible to the needs of individuals and their respective lifestyles. To ensure the best talent is available for our customer’s projects and therefore provide the greatest value for money possible, we will work with our customers and staff to identify the best working arrangements for each individual project.

                        About BAE Systems Applied Intelligence

                        We use our intelligence-led insights to help defend Governments, Nations and Societies from cyber-attacks and financial crime. Our customers depend on our evolving capabilities to help them safely grow their organisations. Our unprecedented access to threat intelligence, world-leading analysts and market-leading technology means we can help them to adapt, evolve and stay ahead of the criminals.

                        Diversity and inclusion are integral to the success of BAE Systems Applied Intelligence. We are proud to have an organisational culture where employees with varying perspectives, skills, life experiences and backgrounds – the best and brightest minds – can work together to achieve excellence and realise individual and organisational potential. We also welcome discussions about flexible working.

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BAE Systems Applied Intelligence

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