EY Digital Factory - Engineering Manager Supervising Associate 

Luxembourg 

432235987

Team & People Leadership

• Build, lead, and retain high-performing engineering teams across one or more domains (backend, frontend, data); set clear goals, provide continuous feedback, and conduct growth-oriented performance conversations.
• Mentor leads and engineers, raising the bar on engineering excellence, code quality, and maintainability; create individualized development plans and promote knowledge sharing.

Delivery & Execution

• Own delivery outcomes for the team(s): plan releases, sequence work, and remove impediments to ensure predictable, on-time delivery of features with the right quality.
• Partner with Product to refine scope, balance trade-oƯs, and align roadmap, capacity, and budgets with strategic objectives.
• Establish lightweight but eƯective execution rituals (planning, reviews, retrospectives) and ensure clear status communication to stakeholders.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Accounting, or a related field.
• 4+ years of experience in data analytics, preferably within an audit or assurance environment.
• Proficiency in SQL, Python, and Spark/PySpark.
• Strong experience in data modeling and transforming complex datasets into structured formats.
• Experience in the financial sector, with a solid understanding of financial data structures.
• Ability to analyze and transcribe financial data into ER diagrams for structured analysis.
• Excellent problem-solving and analytical skills with attention to detail.
• Ability to communicate complex data insights clearly and effectively to non-technical stakeholders.
• Familiarity with data governance, privacy, and compliance standards.
• Experience working in Agile teams and using project management tools like Jira or Trello is a plus.

Technical Stewardship

• Uphold engineering standards for secure, scalable, and observable systems; champion practices such as code reviews, automated testing, CI/CD, and trunk-based development.
• Guide architectural decisions in partnership with domain and enterprise architects; ensure solutions are maintainable, cost-eƯicient, and compliant with reference architectures.
• Oversee technical risk management early in the lifecycle and drive systematic remediation of defects and technical debt.

Quality, Reliability & Operability

• Ensure teams build with reliability and operability in mind (telemetry, SLOs, error budgets, runbooks); promote a blameless incident culture and durable post-incident improvements.
• Coordinate readiness for production, hypercare support, and stable operations in partnership with platform and support functions. Cross-Functional Collaboration.
• Create strong collaboration patterns with Product, Design, Architecture, Security, and Data-aligning design choices to business value and user outcomes.
• Represent engineering in governance and portfolio forums, providing transparent updates on progress, risks, and mitigations. Platform & Reuse.
• Encourage reuse via shared libraries, components, and templates; maintain documentation for architecture decisions and reusable assets.

cations

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. · Demonstrated experience leading software engineering teams as an Engineering Manager or Senior Tech Lead, delivering production systems in one or more domains (backend, frontend, data).
• Strong grasp of modern architectures and practices (microservices/event-driven or modular frontends, data pipelines/lakes/warehouses, cloud-native services, CI/CD, automated testing).
• Proven ability to balance delivery speed with quality, security, and cost; adept at dependency management and stakeholder communication.
• Excellent people leadership, coaching, and conflict-resolution skills; ability tonurture inclusive, high-trust team cultures.

Preferred

• Experience working in an enterprise Digital Factory orplatform/product-led organization.
• Exposure to regulatory and security considerations in financial-services environments.
• Hands-on background in one primary domain (e.g., backend with APIs and services, OR frontend with modern frameworks OR data engineering with pipelines and orchestration) and literacy across adjacent domains.

Tools & Ways of Working

• Proficiency with agile tooling (e.g., Azure DevOps), documentation platforms, and standard code collaboration workflows (PRs, code reviews, trunk-based or GitFlow).
• Familiarity with observability stacks (logs, metrics, traces), automated quality gates, and cloud platforms (Azure).
• Commitment to measurable improvement via engineering metrics (e.g., DORA/SPACE), applied pragmatically to guide coaching and process refinement.

What we offer you

Our offer of employment is contingent upon the successful completion of a background check and pre-screening requirements. The candidate acknowledges that all information provided must be accurate.