James Littlewood

Reading, Berkshire
[email protected]

Professional Profile

Detail-oriented Data Analyst with experience in product data quality, structured validation, categorisation, taxonomy application, SQL analysis and stakeholder communication. Currently supporting accurate eCommerce product data delivery across BAU operations, client implementations and SLA-driven workflows.

Skilled in SQL, Excel, Tableau, Python, Git, Shell and Snowflake fundamentals, with hands-on experience across data analytics, reporting, quality assurance and technical problem-solving. Maintain a personal Ubuntu-based development environment using PostgreSQL, Docker, VS Code Remote SSH and DBeaver to practise database administration, containerised workflows and remote development.

Core Skills, Tools and Technologies

Data and reporting: Excel, Google Sheets, SQL, PostgreSQL, Snowflake fundamentals, Tableau, data cleaning, reporting support and dashboard development

Product and operations data: Product data validation, categorisation, taxonomy application, attribute QA, exception handling, quality checks and SLA-driven delivery

Analysis concepts: Joining and structuring data, data literacy, data modelling fundamentals, statistical fundamentals, dashboard design and communicating insights clearly

Technical tools: Python fundamentals, pandas, regex, Git, Shell, Docker, DBeaver and VS Code

Environments: macOS, Windows, Linux/Ubuntu and remote development workflows

Professional Experience

Technical Data Analyst | Profitero

Aug 2025 – Present

  • Manage product data tasks across assigned clients, markets and client implementations, supporting both day-to-day operations and new client setup work.
  • Maintain and validate identifiers, titles, brands, manufacturers, pack sizes and structured attributes to help ensure accurate product records.
  • Apply client-specific taxonomies, categorisation rules and data standards across multiple retailers and markets, using structured quality checks to maintain consistency.
  • Use Excel and validation checks to review product data at scale, identify inconsistencies, support exception handling and improve accuracy across operational workflows.
  • Investigate inconsistent information, resolve routine discrepancies and escalate ambiguous issues with clear supporting detail.
  • Track workload in JIRA and internal tools, monitor progress against SLAs and communicate blockers, dependencies and risks through team channels.

Team Lead Temporary Secondment | Apple, The Oracle, Reading

Oct 2021 – Apr 2022

  • Led a multifunctional team in a fast-paced technical retail environment, balancing customer escalations, operational priorities and service standards.
  • Monitored performance indicators and operational patterns to improve customer flow, reduce wait times and support decision-making.
  • Collated feedback, identified coaching opportunities and supported training, consistency and service quality across the team.
  • Communicated priorities clearly between colleagues, managers and customers to support smooth daily operations.

Technical Expert / Expert | Apple, The Oracle, Reading

Apr 2015 – Jun 2022

  • Handled complex troubleshooting, diagnostics and repair workflows while working to appointment schedules and service expectations.
  • Used pattern recognition, structured problem-solving and evidence gathering to identify root causes and improve resolution accuracy.
  • Organised workloads, balanced competing priorities and explained technical issues clearly to customers and colleagues.
  • Maintained accurate service notes, repair information and customer records in line with internal processes and quality standards.

Data Analytics Development

Jun 2022 – May 2025

  • Completed structured data analytics training, self-directed technical learning and project work while transitioning towards data and analytics-focused roles.
  • Built foundations in SQL, Excel, Tableau, data analysis, data communication and technical problem-solving.
  • Developed hands-on experience through portfolio projects, online learning and independent technical experimentation.

Projects and Technical Development

Data Analytics Course | The Curious Academy

16-week programme | May 2025 – July 2025

  • Analysed approximately 24 million Chicago bike share records in PostgreSQL to identify usage patterns, behavioural differences and seasonality by member type.
  • Investigated around 350,000 Land Registry records for RG postcode house prices, using PostgreSQL for analysis and Tableau to present findings clearly.
  • Created a Tableau dashboard showing and analysing the performance of the NHL team Anaheim Ducks in comparison with other NHL teams.
  • Applied data cleaning, joins, structured querying, trend interpretation and communication of insights for non-technical audiences.

Further Development | Personal Projects and Learning

  • Built further skills through DataCamp learning across SQL, Excel, data analysis and visualisation, Tableau dashboard development, Snowflake, data modelling fundamentals, Python fundamentals, statistics, data literacy and communicating insights.
  • Maintain a personal Ubuntu-based mini-server environment to build experience with PostgreSQL, Docker, VS Code Remote SSH, DBeaver and remote development workflows.
  • Practise Python fundamentals for data analysis and automation, including pandas, string handling, regex, functions, error handling and structured problem-solving.
  • Explored AI-assisted workflows, prompt design and automation concepts to support productivity, documentation and technical learning.
  • Continue to build technical confidence across macOS, Windows and Ubuntu environments, with a focus on analytics, database and software development workflows.

Education and Certifications

  • BSc (Hons) Audio Engineering and Music Production, SAE Institute / Middlesex University — 2:1
  • Apple iOS / Mac Certified Technician
  • The Curious Academy — Data Analysis Certification

References available on request

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