Mid/Senior Data Engineer (Analytics)

Mid/Senior Data Engineer (Analytics)

T00:00:00.000Z

London

Capabilities

full

Salary: £40k - £80k

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 client sites, and our offices based in London, Sheffield, and Bristol.

What You'll Be Doing as a Data Engineer:

• Lead technical aspects of data engineering projects, providing direction and mentorship to junior and mid-level engineers

• Design and architect modern data solutions that align with business objectives and technical requirements

• Design and implement advanced ETL/ELT pipelines

• Build highly scalable and performant data solutions leveraging cloud platforms and open-source software

• Develop data models to handle enterprise-level analytical needs

• Make critical technical decisions on tools, frameworks, and approaches for complex data challenges

• Optimise large-scale data processing systems for performance and cost-efficiency

• Implement robust data quality frameworks and monitoring solutions

• Evaluate new technologies to enhance our data engineering capabilities

• Collaborate with stakeholders to translate business requirements into technical specifications

• Present technical solutions to leadership and non-technical stakeholders

• 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

• Elevate the technical capabilities of the entire data engineering team

• Help cultivate a data-driven culture within the organisation

• Establish technical standards and patterns that ensure quality and maintainability

You Will Demonstrate:

• Proven experience leading technical aspects of data projects

• Strong data architecture and modelling skills with the ability to design scalable data solutions

• Experience mentoring junior engineers and providing technical guidance

• Deep understanding of data warehouse design principles and methodologies

• Advanced knowledge of optimisation techniques for large-scale data processing

• Strong proficiency in SQL and Python for handling complex data problems

• Hands-on experience with Apache Spark (PySpark or Spark SQL)

• Experience with the Azure data stack

• Knowledge of workflow orchestration tools like Azure Data Factory or Apache Airflow

• Experience with containerisation technologies like Docker

• Proficiency in dimensional modelling techniques

• Experience with CI/CD pipelines for data solutions

• Experience implementing and advocating for test-driven development methodologies in data pipeline workflows, including unit testing, integration testing, and data quality validation frameworks

• Strong communication skills for translating complex technical concepts

• Track record of successful project delivery in a technical leadership capacity

You may also have some of the desirable skills and experience:

• Experience designing and implementing data mesh or data fabric architectures

• Knowledge of cost optimisation strategies for cloud data platforms

• Experience with data quality frameworks and implementation

• Understanding of data lineage and metadata management

• Experience with technical project management

• 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

• Experience with Kubernetes for container orchestration

• Understanding of streaming technologies (Apache Kafka, event-based architectures)

• Software engineering background with SOLID principles understanding

• Experience with high-performance, large-scale data systems

• Knowledge of recent innovations in AI/ML and GenAI

• Defence/Public Sector 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 - 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:

1. Internal Application Review

2. Initial Phone Screen

3. Technical Interview

4. Pair Programming Exercise

5. Final Interview

6. Offer

Working at MA

Methods 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...