At a Glance
- Tasks: Lead data analysis and governance, ensuring data accuracy and optimal pipeline design.
- Company: Join a leading financial services firm committed to social impact and employee well-being.
- Benefits: Generous holiday allowance, private medical insurance, performance bonuses, and learning resources.
- Other info: Inclusive workplace culture that values diversity and empowers all employees.
- Why this job: Make a real difference in data management while working with top industry experts.
- Qualifications: 10+ years in data analysis, expert SQL skills, and strong communication abilities.
The predicted salary is between 63000 - 77000 £ per year.
- We are seeking a highly experienced and analytical
- Lead Data Business Analyst / Data Subject Matter Expert (SME) with
10+ years of proven experience in data analysis, business analysis, and data architecture within enterprise data ecosystems.
In this role, you will serve as the core Subject Matter Expert for Client and Account data flows, end-to-end data lineage, transaction processing, and data governance.
You will bridge the gap between business stakeholders, operations, technology teams, and data engineering to ensure data accuracy, optimal pipeline design, compliance, and actionable business intelligence.
- What You’ll Do
- Data Domain Expertise & Data Flow Architecture
- Serve as the principal SME for Client Master Data, Account Hierarchies, Account Onboarding/Offboarding, KYC/Entity reference data, and downstream data flows.
- Map, document, and maintain end-to-end data lineage and data flow diagrams from source ingestion (CRM, core banking, client onboarding systems) through operational data stores, data lakes/warehouses, to downstream reporting and regulatory consumers.
- Identify data bottlenecks, discrepancies, latency issues, and breakage points across distributed applications and data pipelines.
- Advanced Data Analysis & SQL Engineering
- Write complex, high-performance SQL queries, stored procedures, CTEs, and window functions across relational and distributed databases (e. g., Oracle, Postgre SQL, Snowflake, Teradata) to perform data discovery, reconciliation, profiling, and root-cause analysis.
- Conduct comprehensive data profiling, variance analysis, gap analysis, and trend identification to validate system migrations and data feed integrity.
- Define and implement automated data quality rules, validation scripts, and reconciliation frameworks.
- Business Analysis & Stakeholder Management
- Lead requirement gathering sessions with business leaders, compliance teams, operations, and product managers; translate ambiguous business problems into precise technical specifications, BRDs (Business Requirement Documents), and FRDs (Functional Requirement Documents).
- Define user stories, acceptance criteria, and data dictionary/mapping specifications for engineering and scrum teams in an Agile/Scrum environment.
- Lead User Acceptance Testing (UAT) planning, create complex data test cases, validate data cutover strategies, and oversee test execution.
- Data Governance, Metadata & Quality
- Partner with Data Governance teams to ensure compliance with enterprise data standards, data privacy regulations (GDPR, CCPA), and financial regulatory reporting frameworks (e. g., BCBS 239, Reg reporting).
- Define critical data elements (CDEs), data ownership models, business glossaries, and metadata catalogs for the Client and Account data domains.
- What We’ll Need From You
- Total
Experience: 10+ years of experience as a Data Analyst, Business Analyst, Data SME, or Technical Data Consultant in enterprise environments (preferably Financial Services, Banking, Fin Tech, or Consulting).
- Technical Mastery (SQL): Expert-level proficiency in SQL (complex joins, aggregations, window functions, query optimization, indexing, and debugging data pipelines).
- Domain Knowledge: In-depth, hands‑on domain expertise in Client & Account Data Models, including:
- Client hierarchy management (Ultimate Parent, Immediate Parent, Subsidiary levels).
- Account lifecycles (Creation, Maintenance, Settlement/Clearing, Status Transitions, Closure).
- Counterparty reference data, Party master data, Legal Entity Identifier (LEI) handling.
- Data Flow & Modeling: Proven track record in reverse‑engineering data models, creating Entity-Relationship (ER) diagrams, and mapping source-to-target data interfaces (STTM).
• Tools & Methodologies
- Proficiency in Agile/Scrum delivery models and tools (Jira, Confluence).
- Experience with BI and Data Visualization platforms (Tableau, Power BI, Looker, or Qlik).
- Communication: Exceptional verbal and written communication skills with proven ability to influence senior business executives and technical leads alike.
- What We Can Offer You
We work hard to have a positive financial and social impact on the communities we serve.
In turn, we put our employees first and provide the best-in-class benefits they need to be well, live well and save well.
- Generous holiday allowance starting at 27 days plus bank holidays; increasing with tenure
- A discretional annual performance related bonus
- Private medical insurance packages to suit your personal circumstances
- Employee Assistance Program
- Pension Plan
- Paid Parental Leave
- Special discounts for employees, family, and friends
- Access to an array of learning and development resources
Alongside these benefits Citi is committed to ensuring our workplace is where everyone feels comfortable coming to work as their whole self every day.
We want the best talent around the world to be energized to join us, motivated to stay, and empowered to thrive.
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster.
Lead Data Business Analyst / Data Subject Matter Expert employer: Citi
Citi is an exceptional employer, offering a dynamic work environment that fosters innovation and collaboration within the Equities Technology team. Employees benefit from cutting-edge technology, opportunities for professional growth, and a culture that values diversity and inclusion. With a focus on high-performance analytics and real-time data solutions, Citi empowers its engineers to make impactful contributions while enjoying a supportive atmosphere in a globally recognized financial institution.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Business Analyst / Data Subject Matter Expert
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Citi!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead Data Business Analyst / Data Subject Matter Expert at Citi.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Citi.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Business Analyst / Data Subject Matter Expert at Citi, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Lead Data Business Analyst / Data Subject Matter Expert
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Citi, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Citi. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Citi
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Citi!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
