At a Glance
- Tasks: Lead investment data projects, ensuring quality and reliability while designing advanced data systems.
- Company: Join a forward-thinking company that values innovation and collaboration.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team environment with mentorship opportunities and career advancement.
- Why this job: Make a real impact by transforming complex data into actionable insights for clients.
- Qualifications: Expertise in SQL, data analytics, and strong communication skills required.
The predicted salary is between 63000 - 77000 £ per year.
Job Summary
The Technical Data SME is the domain authority for investment data across client engagements, responsible for the quality, integrity and reliability of the client reporting and investment data delivered to clients.
This role involves designing and overseeing data systems and pipelines, leading complex data analysis, and presenting insights through advanced data visualisation techniques.
The SME collaborates with clients, project management and architecture teams to define customer and company needs, and acts as a senior technical point of contact.
This role requires the ability to merge data from multiple sources and present it in alignment with customer and company requirements, while setting standards and driving continuous improvement in data quality and reliability.
Responsibilities
- Act as the subject matter expert for investment data, providing authoritative guidance on data structures, sourcing, transformation logic and reporting outputs.
- Design, build and optimise efficient, scalable data systems and pipelines, ensuring seamless data flow at volume.
- Lead deep-dive analysis of complex data sets and root cause investigations, delivering clear recommendations and insightful reports to technical and non-technical stakeholders.
- Design and deliver advanced data visualisation and reporting solutions that bring data to life and support data-driven decision making.
- Lead the integration of complex multi-source data into consistent, comprehensive and client-ready outputs.
- Define and drive the strategy for data quality and reliability, establishing controls, monitoring and remediation approaches that uphold the highest standards.
- Develop and implement analytical tools and programmes that empower teams and clients to make data-driven decisions.
- Partner with system architects and product development teams to shape data architecture, influence the technical roadmap and evaluate new technologies.
- Define and maintain data standards, design patterns and best practices, and champion data governance across teams and client engagements.
- Serve as the senior technical contact for clients, advising on solutions, managing expectations and representing the data function in escalations.
- Work with project management to scope work, assess risk and shape delivery plans and timelines.
- Coach and mentor analysts and junior team members, reviewing work and raising technical capability across the team.
Required Skills
- Deep expertise in investment data, including its structures, lifecycle and common data challenges.
- Extensive hands-on experience with SQL and No SQL databases.
- Advanced knowledge of cloud platforms and big data technologies (e. g. AWS, GCP, Azure).
- Strong command of database design and data warehouse principles, including modelling for scale and performance.
- Proven experience designing and delivering data integration and ETL/ELT processes.
- Expert-level data manipulation, data cleansing and transformation techniques.
- Strong knowledge of data governance and best practices in data management.
- Proven ability to work with large datasets and perform data mining at scale.
- Track record of leading complex, client-facing data projects from design through to delivery.
- Demonstrated ability to lead technical decision making and influence senior stakeholders.
- Proven ability to mentor others and raise team capability.
- Continuous improvement mindset for self and team.
- Ability to work collaboratively in a cross-functional team environment.
- Strong computer skills, including proficiency in Microsoft Office.
- Excellent attention to detail and strong documentation skills.
- Outstanding verbal and written communication skills, including presenting to clients and leadership.
- Strong organisational and interpersonal skills.
- Exceptional problem-solving abilities, with the ability to resolve ambiguous, complex issues independently.
Education and Experience
- Bachelor's degree in data analytics, statistics, accounting, computer science, or a related discipline (advanced degree desirable).
- 7+ years of relevant experience in data analytics, reporting and visualisation, including experience in a senior or lead capacity.
Technical Data SME (SQL) in Edinburgh employer: Clearwater Analytics
Clearwater Analytics is an exceptional employer that fosters a collaborative and innovative work culture, making it an ideal place for Reconciliation Associates to thrive. With a strong emphasis on employee growth, we offer comprehensive training and mentorship opportunities, ensuring that our team members are well-equipped to excel in their roles. Located in a dynamic environment, we provide competitive benefits and the chance to work with cutting-edge technology in the investment management sector, all while contributing to the success of our clients and the broader financial community.
StudySmarter Expert Advice🤫
We think this is how you could land Technical Data SME (SQL) in Edinburgh
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We think you need these skills to ace Technical Data SME (SQL) in Edinburgh
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!
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How to prepare for a job interview at Clearwater Analytics
✨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!
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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 Clearwater Analytics!
✨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.
