At a Glance
- Tasks: Build and enhance data platforms to empower business decisions with accurate data.
- Company: Dynamic analytics team in a supportive, learning-focused environment.
- Benefits: Competitive salary, flexible working, 33 days holiday, and wellness initiatives.
- Other info: Opportunity for career growth and a vibrant office in Edinburgh.
- Why this job: Join a culture of experimentation and make a real impact with data.
- Qualifications: Experience with modern data tools and strong SQL skills required.
The predicted salary is between 37500 - 48000 £ per year.
Overview
Department: Engineering
Location: Edinburgh
Compensation: £37,500 - £48,000 / year
Description
Our Analytics Team: The analytics engineering team’s mission is to empower and enable the business to make rigorous and impactful use of data. The analytics engineering team is hiring at mid level to join our team. The role involves building and enhancing our data platform to ensure we collect and make available the data the business needs, while maintaining accuracy and security. The team engages with colleagues to provide knowledge and support, and to carry out detailed analysis requiring specialist knowledge. We believe in a learning culture and encourage self-development. Our regular company hack days provide opportunities to pursue ideas and learn new technologies.
Day-to-day responsibilities
- Ownership of data pipelines, data warehouse and BI tooling
- Sourcing, modelling and making available data required to underpin the company strategy and day-to-day activities
- Maintaining the accuracy and security of our data sources
- Managing stakeholder relationships and priorities in your area of focus
- Promoting pragmatic and effective use of data to drive decision-making
- Training stakeholders across the organisation to improve their use of data
- Supporting stakeholders by carrying out analysis requiring specialist knowledge
- Reducing ambiguity or reconciling disagreement between teams
- Encouraging a culture of experimentation and scientific rigour in the organisation
- Developing and mentoring other members of the team
Tools and environment: Our data platform is AWS based and we use modern tooling around Dagster, dbt, dlt, Redshift and Looker. Prior experience with these tools is beneficial. However, if you have experience with equivalent tools we’d love to hear from you. Recruitment is a chance to bring alternate perspectives into the team.
Skills and experience
- Proficiency with a modern data platform stack
- You have designed and implemented pipelines to process structured and unstructured data to enable stakeholders to solve business problems
- You can demonstrate proficiency with modern data platform languages and tools such as Python, S3, Redshift, Lambda, Dagster, dbt and dlt
- Business intelligence: You are proficient in SQL for data modelling and transformation
- You have developed data models to enable stakeholders to self-serve business questions by using BI software such as Looker
- Supporting decision making: You have created appropriately designed reports and visualisations to support non-technical audiences
- You have experience designing, running and analysing the results of A/B tests with business stakeholders
- Stakeholder management: You have a demonstrable ability to manage your own work backlog in collaboration with leadership and business stakeholders in a commercial setting
- You are comfortable working with the team to answer questions from stakeholders
Work life and environment
We believe in a strong work-life balance. We typically operate a 35-hour working week and have a well-equipped Edinburgh HQ designed for collaboration with high-quality A/V equipment to support distributed teams. We support a no-blame culture. Our mindset is: work hard, be nice to people, and the rest will sort itself out.
Work pattern for this role
This is a permanent, full-time role (Monday to Friday, 9am to 5pm). It will be based in our Edinburgh office, with an opportunity for hybrid working (2 days in the office and 3 days at home each week). We are moving to a new office in the west of Edinburgh next year, with enhanced facilities and easy transport links. Further details will be shared as you go through the hiring process.
Perks
- Mid-level annual starting salary of £37,500 - £48,000 per annum, depending on experience, with room to progress to £55,500 within the band. Salaries are linked to performance expectations to support a culture of fairness, learning and development.
- 33 days holiday (plus one extra day for each year you are with us)
- Flexible/hybrid working
- Private health care
- Life assurance
- 5% matched pension contributions
- Summer 4-day weeks (eight additional days off)
- Buy-as-you-earn share schemes
- Sabbatical leave (unpaid)
- Cycle to work scheme
- Wellness webinars
- Focused learning time and learning budgets
- Volunteering day
Find out more about our benefits package here. We are an equal opportunities employer and encourage applications from people with varied backgrounds and perspectives. All applicants are considered for employment without regard to ethnicity, religion, sexual orientation, gender identity, age, disability, family or parental status.
Analytics Engineer (Mid level) employer: FreeAgent
Join our dynamic Analytics Team in Edinburgh, where we foster a culture of learning and innovation. With a strong emphasis on work-life balance, flexible hybrid working options, and a commitment to employee development, we offer an environment that encourages personal growth and collaboration. Our competitive benefits package, including generous holiday allowances and wellness initiatives, makes us an exceptional employer for those seeking meaningful and rewarding careers in data analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer (Mid level)
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or attend industry meetups. It’s all about making connections that can help us get our foot in the door.
✨Tip Number 2
Prepare for those interviews by practising common questions and showcasing your skills with real examples. We want to show how our experience aligns with the role and the company culture.
✨Tip Number 3
Don’t forget to follow up after interviews! A quick thank-you email can keep us fresh in their minds and show our enthusiasm for the role.
✨Tip Number 4
Apply through our website! It’s the best way to ensure our application gets seen by the right people. Plus, we can tailor our application to highlight how we fit the Analytics Engineer role perfectly.
We think you need these skills to ace Analytics Engineer (Mid level)
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Analytics Engineer role. Highlight your experience with data platforms and tools like Python, SQL, and AWS, as well as any relevant projects that showcase your skills.
Showcase Your Problem-Solving Skills:We love seeing how you tackle challenges! Include examples of how you've designed data pipelines or created reports that helped stakeholders make informed decisions. This will demonstrate your ability to drive impact through data.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language and avoid jargon where possible. We appreciate a well-structured application that makes it easy for us to see your qualifications and fit for the role.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at FreeAgent
✨Know Your Tools Inside Out
Make sure you’re familiar with the tools mentioned in the job description, like AWS, Dagster, and Looker. Brush up on your SQL skills too, as you'll likely be asked to demonstrate your proficiency during the interview.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've designed and implemented data pipelines or solved business problems using data. Be ready to discuss specific challenges you faced and how you overcame them, as this will highlight your analytical thinking.
✨Engage with Stakeholder Scenarios
Think about past experiences where you managed stakeholder relationships. Be prepared to discuss how you prioritised their needs and communicated effectively, as this role involves a lot of collaboration and support.
✨Embrace the Learning Culture
Since the company values self-development, come prepared to talk about how you’ve pursued learning opportunities in the past. Mention any relevant courses, hack days, or personal projects that showcase your commitment to growth and experimentation.
