Lead Data Engineer

With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility.

Role Summary and Purpose

Reporting to the Head of Enterprise Data, we are seeking a Lead Data Engineer with deep expertise in Data Vault design and a proven track record of delivering high‑quality data solutions. You will partner closely with our technology and development leads to define, shape, and implement Arch’s data architecture and data management practices. This is a dynamic, hands‑on role ideal for someone who is passionate about technology and motivated by the opportunity to drive meaningful, long‑term impact across the organisation’s data landscape.

Key Responsibilities Include

• Landscape Understanding & Platform Support: Lead the effort to establish a clear view of our current database and application estate, supporting operations in maintaining, rationalising, and optimising existing data platforms.
• Strategic Platform Development: Help design and build the strategic data platforms Arch is moving toward, ensuring they are robust, scalable, and aligned with business needs.
• Standards, Tooling & Best Practices: Define and implement the tools, patterns, and practices required to deliver efficient, high‑quality, and data‑driven engineering solutions.
• Technology Evangelism: Act as an advocate for modern data engineering approaches, championing innovation and continuous improvement across teams.
• Innovation & Awareness: Stay current with emerging technologies, techniques, and capabilities—applying relevant advancements to improve delivery and engineering effectiveness.
• Leadership & Problem Solving: Demonstrate strong leadership behaviours, paired with practical operational experience and an ability to tackle complex technical challenges.
• Collaboration & Roadmap Shaping: Work closely with architecture and technology leaders to define the roadmap for evolving Arch’s data engineering practices, grounded in industry trends and current organisational capabilities.

To excel in this role, you’ll combine deep technical expertise with a hands‑on, delivery‑focused mindset, driving data initiatives that improve the efficiency, agility, and value of Arch’s data ecosystem.

Key Tasks and Responsibilities

• Arch Operations: Collaborate with business stakeholders to translate requirements into actionable technical tasks and ensure their successful delivery. Work with ancillary teams to support the data warehouse, driving improvements in data quality, reporting, and coordination with source system teams. Partner closely with the data architecture team to enhance the data warehouse, contributing to design discussions, reviewing architectural plans, and ensuring alignment with best‑practice standards.
• AEIS Data Warehouse: Operate effectively within agile sprint teams, contributing to sprint planning, daily stand‑ups, and reviews while supporting continuous improvement of team processes. Design, build, and manage ELT processes to integrate data from multiple sources into the data warehouse, ensuring consistency and quality across systems. Monitor and optimise data pipelines to ensure reliable, efficient operation. Maintain a strong focus on data quality, demonstrating attention to detail and rigorous validation practices. Deliver high‑quality code end‑to‑end — including design, implementation, unit testing, refactoring, and documentation. Automate deployment processes to ensure consistent, repeatable, and reliable releases. Monitor automated systems, proactively identifying and resolving issues. Write, maintain, and improve unit tests to ensure code quality and early issue detection. Collaborate with developers to improve test coverage, reliability, and overall engineering standards. Ensure all new code meets established standards for readability, performance, security, and documentation, including performing and participating in code reviews. Apply DevSecOps principles to integrate security into all stages of the development lifecycle. Integrate and manage tools across the data stack — including ETL platforms, orchestration tools, and data management components — ensuring seamless interoperability and optimal performance. Continuously learn and experiment with modern technologies, applying new knowledge to improve systems, processes, and overall engineering maturity. Stay informed on industry trends, using this insight to drive innovation and optimise data engineering practices.

Experience Requirements and Skills

• Extensive hands‑on experience designing, developing, and maintaining data pipelines and ETL/ELT processes.
• Data Vault 2.0 certification highly desirable.
• Expert‑level experience with Snowflake or other cloud‑based data warehouse technologies.
• Strong hands‑on experience with orchestration tools such as Airflow (or equivalent).
• Deep knowledge of relational and non‑relational databases, including RDBMS proficiency and modern data warehouse design.
• Familiarity with DevOps practices, CI/CD pipelines, automation, and containerisation technologies (e.g., Docker, Harness, Kubernetes).
• Knowledge of cloud‑native architectures and modern application frameworks, including REST APIs, microservices, Spring Boot/.NET Core, GitHub, Jenkins, OpenShift, BPM, SQL, Oracle, NoSQL, AMQP/Kafka.
• Strong understanding of private cloud, IaaS, PaaS, and SaaS models, with extensive experience across Azure and AWS.
• Broad understanding of modern software engineering methods, tools, and best practices.
• Proficiency in SQL (including ANSI SQL) and experience with Python or other programming languages used in data engineering.
• Experience with application and data testing automation tools and best practices.
• Strong grounding in agile methodologies, with proven experience applying them to large‑scale technology delivery.
• Strong strategic thinking and long‑term planning capabilities, with the ability to balance ideal architectural solutions against pragmatic business needs.
• Excellent communication and interpersonal skills for collaborating with diverse technical and non‑technical stakeholders.
• Strong analytical, problem‑solving, and decision‑making skills, with a focus on delivering reliable, scalable, and high‑quality solutions.

Experience & Education

Required knowledge and skills are typically obtained through a Bachelor’s degree (or equivalent experience) and 10+ years of relevant experience in software development, systems infrastructure, and architecture design — including project management, business analysis, and hands‑on data engineering. Data Vault 2.0 certification is highly preferred.