At a Glance
- Tasks: Design and implement data solutions using Python, SQL, and Apache Airflow.
- Company: Methods Analytics improves society by helping people make better decisions with data.
- Benefits: Enjoy remote work, 25 days annual leave, wellness programmes, and a supportive environment.
- Why this job: Join a team that values creativity, ethics, and making a real impact in society.
- Qualifications: Experience in SQL, Python, ETL processes, and cloud technologies is essential.
- Other info: Security clearance required; expect a transparent hiring process.
The predicted salary is between 36000 - 60000 £ per year.
Methods Analytics (MA) is recruiting for a Data Engineer to join our team a permanent basis.This role will be mainly remote but require flexibility to travel to Bristol.What You\’ll Be Doing as a Data Engineer:Design and architect modern data solutions that align with business objectives and technical requirementsDesign and implement advanced ETL/ELT pipelines using Python, SQL, and Apache AirflowBuild highly scalable and performant data solutions leveraging cloud platforms and technologiesDevelop complex data models to handle enterprise-level analytical needsMake critical technical decisions on tools, frameworks, and approaches for complex data challengesOptimise large-scale data processing systems for performance and cost-efficiencyImplement robust data quality frameworks and monitoring solutionsEvaluate new technologies to enhance our data engineering capabilitiesCollaborate with stakeholders to translate business requirements into technical specificationsPresent technical solutions to leadership and non-technical stakeholdersContribute to the development of the Methods Analytics Engineering Practice by participating in our internal community of practiceYour Impact:Enable business leaders to make informed decisions with confidence through timely, accurate data insightsDrive adoption of modern data architectures and platformsDeliver seamless data solutions that enhance user experienceElevate the technical capabilities of the entire data engineering teamHelp cultivate a data-driven culture within the organisationEstablish technical standards and patterns that ensure quality and maintainabilityRequirementsExperience in SQL Server Integration Services (SSIS)Good experience with ETL – SSIS, SSRS, T-SQL (On-prem/Cloud)Strong proficiency in SQL and Python for handling complex data problemsHands-on experience with Apache Spark (PySpark or Spark SQL)Experience with the Azure data stackKnowledge of workflow orchestration tools like Apache AirflowExperience with containerisation technologies like DockerProficiency in dimensional modelling techniquesExperience with CI/CD pipelines for data solutionsExperience implementing and advocating for test-driven development methodologies in data pipeline workflows, including unit testing, integration testing, and data quality validation frameworksStrong communication skills for translating complex technical conceptsTrack record of successful project delivery in a technical leadership capacityYou may also have some of the desirable skills and experience:Experience designing and implementing data mesh or data fabric architecturesKnowledge of cost optimisation strategies for cloud data platformsExperience with data quality frameworks and implementationUnderstanding of data lineage and metadata managementExperience with technical project managementExperience with data visualisation tools like Power BI or Apache SupersetExperience with other cloud data platforms like AWS, GCP or OracleExperience with modern unified data platforms like Databricks or Microsoft FabricExperience with Kubernetes for container orchestrationUnderstanding of streaming technologies (Apache Kafka, event-based architectures)Software engineering background with SOLID principles understandingExperience with high-performance, large-scale data systemsKnowledge of recent innovations in AI/ML and GenAIDefence or Public Sector experienceConsultant experienceSecurity Clearance:UKSV (United Kingdom Security Vetting) clearance is required for this role, with Security Check (SC) as the minimum standard.Our Hiring ProcessAt Methods Analytics, we believe in a transparent hiring process. Here\’s what you can expect:1. Internal Application Review2. Initial Phone Screen3. Technical Interview4. Pair Programming Exercise5. Final Interview6. OfferBenefitsWorking at MAMethods Analytics (MA) exists to improve society by helping people make better decisions with data. Combining passionate people, sector-specific insight, and technical excellence to provide our customers an end-to-end data service.We use a collaborative, creative and user centric 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 – 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 out colleagues to develop the things they are good at and enjoy.By joining us you can expectAutonomy to develop and grow your skills and experienceBe part of exciting project work that is making a difference in societyStrong, inspiring, and thought-provoking leadershipA supportive and collaborative environmentAs well as this, we offer:Development access to Pluralsight and LinkedIn LearningWellness 24/7 Confidential employee assistance programmeSocial – office parties, pizza Friday and commitment to charitable causesTime off – 25 days of annual leave a year, plus bank holidays, with the option to buy 5 extra days each yearVolunteering – 2 paid days per year to volunteer in our local communities or within a charity organisationPension Salary Exchange Scheme with 4% employer contribution and 5% employee contributionDiscretionary Company Bonus based on company and individual performanceLife Assurance of 4 times base salaryPrivate Medical Insurance which is non-contributory (spouse and dependants included)Worldwide Travel Insurance which is non-contributory (spouse and dependants included) #J-18808-Ljbffr
(SC cleared) Data Engineer employer: JobLeads GmbH
Contact Detail:
JobLeads GmbH Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land (SC cleared) Data Engineer
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Apache Airflow, SQL Server Integration Services (SSIS), and Azure data stack. Having hands-on experience or projects that showcase your skills with these tools can set you apart during the interview process.
✨Tip Number 2
Prepare to discuss your previous experiences with data engineering projects, particularly those involving ETL/ELT pipelines and cloud platforms. Be ready to explain your decision-making process and how you optimised data solutions for performance and cost-efficiency.
✨Tip Number 3
Since communication is key in this role, practice explaining complex technical concepts in simple terms. You may need to present your ideas to non-technical stakeholders, so being able to convey your thoughts clearly will be crucial.
✨Tip Number 4
Engage with the data engineering community online, whether through forums, webinars, or local meetups. Networking can provide insights into industry trends and may even lead to referrals, increasing your chances of landing the job with us.
We think you need these skills to ace (SC cleared) Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the Data Engineer role. Focus on your proficiency in SQL, Python, and any experience with ETL processes, cloud platforms, and data modelling.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and how your background fits the company's mission. Mention specific projects or experiences that demonstrate your ability to solve complex data challenges.
Highlight Technical Skills: In your application, emphasise your technical skills such as experience with Apache Airflow, Azure data stack, and containerisation technologies like Docker. Be specific about your hands-on experience with these tools.
Showcase Communication Skills: Since strong communication skills are essential for this role, include examples of how you've successfully translated complex technical concepts to non-technical stakeholders in previous positions.
How to prepare for a job interview at JobLeads GmbH
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, Python, and ETL processes in detail. Highlight specific projects where you've implemented these technologies, especially using Apache Airflow or Azure data stack, as this will demonstrate your hands-on expertise.
✨Understand the Company Culture
Research Methods Analytics and their approach to data solutions. Familiarise yourself with their values around ethics, privacy, and collaboration. This will help you align your answers with their mission and show that you're a good cultural fit.
✨Prepare for Technical Challenges
Expect technical questions or exercises during the interview process. Brush up on your knowledge of data modelling, cloud platforms, and containerisation technologies like Docker. Practising coding challenges can also be beneficial.
✨Communicate Clearly
Strong communication skills are essential for this role. Practice explaining complex technical concepts in simple terms, as you'll need to present solutions to both technical and non-technical stakeholders. This will showcase your ability to bridge the gap between tech and business.