Data Analyst

Data Analyst at Barclays

Join us as a Data Analyst at Barclays, where you'll be instrumental in building analytical tools to generate insights, recognize patterns, and predict behavior. You will deliver compelling content directly to users of information products, working closely with technical teams, architects, designers, and administrators to overcome challenges and bring solutions to life.

Role Purpose

The primary purpose of this role is to enable data-driven strategic and operational decision-making. This is achieved by extracting actionable insights from large datasets, performing statistical and advanced analytics to uncover trends and patterns, and presenting findings through clear visualizations and reports.

What you'll do

• Investigate and analyze data issues related to quality, lineage, controls, and authoritative source identification. Document data sources, methodologies, and quality findings with recommendations for improvement.
• Design and build robust data pipelines to automate data movement and processing efficiently.
• Apply advanced analytical techniques to large datasets to uncover trends and correlations, develop validated logical data models, and translate these insights into actionable business recommendations, leveraging machine learning/AI for operational and process improvements.
• Through data-driven analysis, translate analytical findings into clear, actionable business recommendations, identifying specific opportunities for operational and process enhancements.
• Design and create interactive dashboards and visual reports using appropriate tools, and automate reporting processes to meet both regular and ad-hoc stakeholder requirements.

Basic/Essential Skills

To be successful as a Data Analyst, you should have experience with:

Core Technical Expertise

• Expert-level SQL: analytical queries, query optimization, complex transformations, performance tuning.
• Lakehouse table formats: Delta Lake, Apache Iceberg.
• Data modeling: dimensional modeling, SCD Type 1/2/3.
• Object storage & file formats: S3, Parquet.
• Data transformation frameworks: dbt, Databricks.

Data Quality, Governance & Metadata

• Metadata management, lineage, and data catalogs.
• Fine-grained access control, PII handling, and data masking.

Cloud & Platform Expertise

• Deep experience with at least one cloud platform (AWS).
• Hands-on expertise with lakehouse platforms (Databricks, Snowflake + Iceberg).

Functional Skills

• Strong understanding of business data requirements and KPIs.
• Ability to translate business logic into curated datasets and metrics.
• Data analysis mindset: identify anomalies, trends, and data issues.
• Stakeholder collaboration with analytics, BI, and product teams.
• Documentation of business rules, data definitions, and assumptions.
• Understanding of data lifecycle, data ownership, and stewardship.

Educational Qualification

• Graduation as a minimum.

Analyst Expectations

• Perform prescribed activities in a timely manner and to a high standard, consistently driving continuous improvement.
• Requires in-depth technical knowledge and experience in the assigned area of expertise.
• Thorough understanding of the underlying principles and concepts within the area of expertise.
• Will have an impact on the work of related teams within the area and partner with other functions and business areas.
• Takes responsibility for end results of a team's operational processing and activities.
• Escalate breaches of policies/procedures appropriately and take responsibility for embedding new policies/procedures adopted due to risk mitigation.
• Advise and influence decision-making within own area of expertise and take ownership for managing risk and strengthening controls.
• Deliver work in line with relevant rules, regulation, and codes of conduct.
• Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organization's products, services, and processes.
• Demonstrate understanding of how areas coordinate and contribute to the achievement of organizational objectives.
• Make evaluative judgments based on the analysis of factual information, paying attention to detail.
• Resolve problems by identifying and selecting solutions through the application of acquired technical experience, guided by precedents.
• Guide and persuade team members and communicate complex/sensitive information.
• Act as a contact point for stakeholders outside of the immediate function, while building a network of contacts both internally and externally.
• (For People Leaders) Lead and supervise a team, guiding professional development, allocating work, and coordinating resources, demonstrating the LEAD behaviors: Listen and be authentic, Energize and inspire, Align across the enterprise, Develop others.
• (For Individual Contributors) Develop technical expertise in work area, acting as an advisor where appropriate.

Barclays Values & Mindset

All colleagues are expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge, and Drive – the operating manual for how we behave.

Key skills/competency

• SQL
• Data Modeling
• Cloud Platforms (AWS)
• Lakehouse Platforms (Databricks/Snowflake)
• Data Quality
• Predictive Analytics
• Data Visualization
• Business Intelligence
• Stakeholder Management
• ETL (dbt)