At a Glance
- Tasks: Develop and enhance data platforms using SQL, ETL, and AI solutions.
- Company: Leading investment management firm with a focus on technology and innovation.
- Benefits: Competitive salary, career growth, and the chance to work with cutting-edge tech.
- Other info: Collaborative environment with real ownership and visibility in projects.
- Why this job: Transform data analysis into impactful engineering and automation roles.
- Qualifications: Strong SQL skills, experience with ETL and cloud platforms like Snowflake.
The predicted salary is between 63000 - 77000 £ per year.
I\'m recruiting on behalf of a leading investment management firm looking for a
Senior Data Analyst to join its growing technology team.
This isn\'t a traditional reporting role.
You\'ll play a key part in developing and improving the firm\'s data platform, working across SQL, ETL, Snowflake, data quality and automation while helping introduce practical AI solutions across the business.
Working closely with stakeholders across Investments, Operations, Finance and Technology, you\'ll solve complex data challenges, improve processes and help ensure business-critical data is accurate, reliable and fit for purpose.
The Role
- Develop and maintain SQL-based data pipelines and ETL processes.
- Support and enhance the firm\'s Snowflake data platform.
- Improve data quality through validation, reconciliation and monitoring.
- Identify opportunities to automate manual processes using modern technologies and AI.
- Partner with business stakeholders to deliver scalable data solutions.
- Support data governance, reporting and continuous improvement initiatives.
- What You\'ll Need
- Strong SQL skills and experience working with large datasets.
- Experience with ETL processes and cloud-based data platforms such as Snowflake.
- Knowledge of data quality, validation and governance.
- Python and/or Power BI experience would be beneficial.
- An interest in automation and emerging AI technologies.
- Strong analytical, problem-solving and stakeholder management skills.
- Experience within financial services or another regulated environment is advantageous.
Why Apply?
- Move beyond traditional data analysis into a broader data engineering and automation role.
- Work with modern technologies including Snowflake and AI.
- Join a collaborative business where you\'ll have real ownership and visibility.
- Help shape how data is managed and used across the organisation.
- #J-18808-Ljbffr
Senior Data Analyst employer: Harrington Starr
Join a leading high-volume futures trading organisation in London, where you will play a pivotal role in ensuring the stability of critical trading and clearing platforms. With a strong focus on employee growth and a collaborative work culture, this company offers competitive daily rates and long-term contract opportunities, making it an excellent employer for those seeking meaningful and rewarding careers in the capital markets sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analyst
✨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 Harrington Starr!
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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 Harrington Starr.
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When you find a suitable opening like Senior Data Analyst at Harrington Starr, 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 Senior Data Analyst
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 Harrington Starr, 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 Harrington Starr. 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 Harrington Starr
✨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 Harrington Starr!
✨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.
