Senior Data Engineer

Summary

Join Methods Analytics as a Senior Data Engineer and lead technical aspects of data engineering projects, mentoring junior engineers. You will design and implement modern data solutions using various technologies like Python, SQL, and Apache Airflow on cloud platforms. This primarily remote role requires flexibility for travel to client sites and offices in London, Sheffield, and Bristol. You'll be responsible for building scalable and performant data solutions, optimizing systems, and implementing robust data quality frameworks. The role demands strong technical leadership, communication, and collaboration skills. UKSV clearance is required.

Requirements

• 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 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
• 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

Responsibilities

• 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 using Python, SQL, and Apache Airflow
• Build highly scalable and performant data solutions leveraging cloud platforms and technologies
• Develop complex 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

Preferred Qualifications

• 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 or Public Sector experience
• Consultant experience
• Willingness to obtain DV clearance

Benefits

• Development access to Pluralsight and LinkedIn Learning
• Wellness 24/7 Confidential employee assistance programme
• Social - office parties, pizza Friday and commitment to charitable causes
• Time off - 25 days of annual leave a year, plus bank holidays, with the option to buy 5 extra days each year
• Volunteering - 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
• Discretionary Company Bonus based on company and individual performance
• Life Assurance of 4 times base salary
• Private Medical Insurance which is non-contributory (spouse and dependants included)
• Worldwide Travel Insurance which is non-contributory (spouse and dependants included)