At a Glance
- Tasks: Transform raw data into powerful insights and build scalable data solutions.
- Company: Join Methods Analytics, a forward-thinking company dedicated to improving society with data.
- Benefits: Enjoy competitive salary, remote work, wellness support, and generous leave policies.
- Why this job: Make a real impact by enabling informed decisions through innovative data solutions.
- Qualifications: Proficiency in SQL and Python, with experience in ETL/ELT pipelines.
- Other info: Collaborative environment with strong career growth and exciting project opportunities.
The predicted salary is between 32000 - 48000 ÂŁ per year.
Methods Analytics (MA) is recruiting for a Data Engineer to join our team on a permanent basis. This role will be mainly remote but require flexibility to travel to client sites, and our offices based in London, Sheffield, and Bristol.
What You'll Be Doing as a Data Engineer:
- Work closely with crossâfunctional teams, translating complex technical concepts into clear, accessible language for nonâtechnical audiences.
- Collaborate with a dynamic delivery team on innovative projects, transforming raw data into powerful insights.
- Design and implement efficient ETL and ELT pipelines using modern tools such as Python, SQL, and Apache Airflow.
- Build scalable data solutions leveraging cloud platforms and technologies.
- Develop and maintain sophisticated data models, employing dimensional modelling techniques to support comprehensive data analysis and reporting.
- Implement best practices in data governance, security, and compliance to maintain data integrity.
- Ensure data quality through rigorous QA processes, continuously refining and optimising data queries.
- Develop intuitive dashboards that provide actionable insights to stakeholders.
- Monitor and tune solution performance to enhance reliability, speed, and functionality of data systems.
- Stay ahead of industry trends, continuously enhancing your skills with the latest data engineering tools and methodologies.
- Contribute to the development of the Methods Analytics Engineering Practice by participating in our internal community of practice.
Your Impact:
- Enable business leaders to make informed decisions with confidence through timely, accurate data insights.
- Drive adoption of modern data architectures and platforms.
- Deliver seamless data solutions that enhance user experience.
- Help cultivate a dataâdriven culture within the organisation.
You Will Demonstrate:
- Strong proficiency in SQL and Python for handling complex data problems.
- Experience building and optimising ETL/ELT pipelines.
- Handsâon experience with Apache Spark (PySpark or Spark SQL).
- Experience with the Azure data stack.
- Knowledge of workflow orchestration tools like Apache Airflow.
- Experience with containerisation technologies (Docker).
- Ability to craft efficient and performant queries.
- Proficiency in dimensional modelling techniques.
- Experience with CI/CD pipelines for data solutions.
- Familiarity with testâdriven development principles applied to data pipeline construction and validation.
- Strong communications skills for translating technical concepts to nonâtechnical audiences.
- Business requirements analysis and translation into technical specifications.
You may also have some of the desirable skills and experience:
- Experience with data visualisation tools like Power BI or Apache Superset.
- Experience with other cloud data platforms like AWS, GCP or Oracle.
- Experience with modern unified data platforms like Databricks or Microsoft Fabric.
- Familiarity with modern data lakehouse architectures.
- Knowledge of legacy ETL tools like SSIS.
- Experience with Kubernetes for container orchestration.
- Understanding of streaming technologies (Apache Kafka, eventâbased architectures).
- Software engineering background with SOLID principles understanding.
- Experience with data governance tools.
- Experience with highâperformance, largeâscale data systems.
- Familiarity with Agile development methodologies.
- Knowledge of recent innovations in AI/ML and GenAI.
- Defence or Public Sector experience.
- Consultant experience.
Security Clearance:
UKSV (United Kingdom Security Vetting) clearance is required for this role, with Security Check (SC) as the minimum standard, either already held or with a willingness to undergo the process. Some roles/projects may require Developed Vetting (DV) clearance; while not mandatory, a willingness to obtain DV clearance would be beneficial. As part of the onboarding process candidates will be asked to complete a Baseline Personnel Security Standard (BPSS); details of the evidence required to apply may be found on the government website GOV.UK â Government baseline personnel security standard. If you are unable to meet this and any associated criteria, then your employment may be delayed, or rejected. Details of this will be discussed with you at interview.
Our Hiring Process
At Methods Analytics, we believe in a transparent hiring process. Here's what you can expect:
- Internal Application Review
- Initial Phone Screen
- Technical Interview
- Collaborative Pair Programming Exercise
- Final Interview
- Offer
Working at MA
Methods Analytics (MA) exists to improve society by helping people make better decisions with data. Combining passionate people, sectorâspecific insight, and technical excellence to provide our customers an endâtoâend data service.
We use a collaborative, creative and userâcentric approach to data to do good and solve difficult problems. Ensuring that our outputs are transparent, robust, and transformative.
We value discussion and debate as part of our approach. We will question assumptions, ambition, and process â but do so with respect and humility.
We relish difficult problems, and overcome them with innovation, creativity, and technical freedom to help us design optimum solutions. Ethics, privacy, and quality are at the heart of our work, and we will not sacrifice these for outcomes.
We treat data with respect and use it only for the right purpose. Our people are positive, dedicated, and relentless. Data is a vast topic, but we strive for interactions that are engaging, informative and fun in equal measure. But maintain a steely focus on outcomes and delivering quality products for our customers.
We are passionate about our people; we want our colleagues to develop the things they are good at and enjoy.
By joining us you can expect:
- Autonomy to develop and grow your skills and experience.
- Be part of exciting project work that is making a difference in society.
- Strong, inspiring, and thoughtâprovoking leadership.
- A supportive and collaborative environment.
As well as this, we offer:
- Development access to Pluralsight and LinkedIn Learning.
- Wellness 24/7 Confidential employee assistance programme.
- Socialâoffice parties, pizza Friday and commitment to charitable causes.
- Time off â 25 days of annual leave a year, plus bank holidays, with the option to buy 5 extra days each year.
- Volunteering â 2 paid days per year to volunteer in our local communities or within a charity organisation.
- Pension Salary Exchange Scheme with 4% employer contribution and 5% employee contribution.
- Life Assurance of 4 times base salary.
- Private Medical Insurance which is nonâcontributory (spouse and dependants included).
- Worldwide Travel Insurance which is nonâcontributory (spouse and dependants included).
Data Engineer (Analytics) in London employer: Methods Business and Digital Technology
Contact Detail:
Methods Business and Digital Technology Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Data Engineer (Analytics) in London
â¨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
â¨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving SQL, Python, or any cool data visualisations. This gives hiring managers a taste of what you can do beyond just a CV.
â¨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios related to data engineering. Donât forget to brush up on explaining complex concepts in simple terms â itâs key for collaborating with non-technical teams!
â¨Tip Number 4
Apply through our website! Itâs the best way to ensure your application gets seen by the right people. Plus, youâll be part of a community that values innovation and collaboration in data solutions.
We think you need these skills to ace Data Engineer (Analytics) in London
Some tips for your application đŤĄ
Tailor Your Application: Make sure to customise your CV and cover letter for the Data Engineer role. Highlight your experience with SQL, Python, and any relevant projects that showcase your skills in building ETL/ELT pipelines. We want to see how you can bring value to our team!
Showcase Your Communication Skills: Since you'll be translating complex technical concepts for non-technical audiences, it's crucial to demonstrate your communication prowess. Use clear language in your application to show us you can bridge the gap between tech and business.
Highlight Relevant Experience: Donât forget to mention any hands-on experience with tools like Apache Airflow or Azure data stack. If you've worked on data visualisation or governance, let us know! We love seeing how your background aligns with our needs.
Apply Through Our Website: We encourage you to apply directly through our website. Itâs the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining our community at Methods Analytics!
How to prepare for a job interview at Methods Business and Digital Technology
â¨Know Your Tech Inside Out
Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss how you've used these tools in past projects, especially when it comes to building and optimising ETL/ELT pipelines.
â¨Showcase Your Problem-Solving Skills
Prepare to share specific examples of complex data problems you've tackled. Highlight your experience with Apache Spark or any cloud platforms like Azure, and explain how you approached these challenges.
â¨Communicate Clearly
Since you'll be translating technical concepts for non-technical audiences, practice explaining your work in simple terms. This will demonstrate your strong communication skills and ability to collaborate with cross-functional teams.
â¨Stay Current with Industry Trends
Familiarise yourself with the latest data engineering tools and methodologies. Mention any recent innovations in AI/ML or data lakehouse architectures that excite you, showing your passion for continuous learning.