At a Glance
- Tasks: Transform and analyse customer data in a dynamic, high-impact environment.
- Company: Join a tech-led organisation with a strong data-driven culture.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborate with Data Science teams in an evolving project landscape.
- Why this job: Make a real impact on data strategy and drive meaningful change from day one.
- Qualifications: Strong SQL and dbt skills, with experience in Snowflake and data engineering.
The predicted salary is between 60750 - 74250 £ per year.
Contract Analytical / Data Engineer
This is an opportunity to join a high-impact data programme at a pivotal stage, moving from strategy into execution.
You'll work within an established Snowflake and dbt environment, helping shape how customer and prospect data is transformed, analysed and operationalised across the business.
The project requires someone who can quickly understand complex existing data models and deliver meaningful change from day one.
The Company
They are a technology-led organisation with a mature data ecosystem and a strong culture of data-driven decision making.
Their teams are focused on improving how customer and prospect data supports commercial and operational outcomes.
With a large-scale Snowflake environment and extensive dbt implementation already in place, they are investing heavily in the next phase of their data strategy.
The team works closely with Data Science and business stakeholders to deliver practical, high-value outcomes.
The Role and Deliverables
- Investigate existing dbt models, data pipelines and Snowflake schemas to understand data flows and dependencies.
- Analyse data lineage across source systems, transformations and downstream data exposures.
- Build new data exposures and enhance existing models to support evolving business requirements.
- Modify transformation logic and validate the impact of changes through data analysis and testing.
- Support scenario modelling, data quality initiatives, QA activities and operational readiness.
- Collaborate with engineering, analytics and Data Science stakeholders while working autonomously in an evolving project environment.
- Your Skills & Experience
- Strong Data Engineering experience within modern cloud data environments.
- Excellent SQL skills and deep hands-on expertise with dbt.
- Strong experience working with Snowflake.
- Demonstrated ability to understand and navigate complex existing data models, schemas and transformation pipelines.
- Experience tracing data lineage and assessing the downstream impact of engineering changes.
- Strong analytical skills, with the ability to validate and troubleshoot data outputs.
- Comfortable working in environments where requirements evolve over time.
- Proven ability to operate independently and quickly become productive in established data estates.
- Experience with Python is beneficial.
- Experience partnering with Data Science teams or working with customer and operational data is advantageous.
- Familiarity with AI-assisted engineering workflows is beneficial.
Analytical Engineer in London employer: Harnham
As a leading specialist data consultancy, we pride ourselves on fostering a collaborative and innovative work culture that empowers our Analytics Engineering Consultants to thrive. With a focus on professional development, we offer extensive growth opportunities and the chance to work on high-impact projects across diverse industries, all while enjoying the flexibility of remote work in the UK. Join us to be part of a team that values your expertise and encourages you to influence strategy and drive meaningful change for our clients.
StudySmarter Expert Advice🤫
We think this is how you could land Analytical Engineer in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Analytical Engineer in London
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 Harnham, 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 Harnham. 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 Harnham
✨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 Harnham!
✨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.
