Digital Factory - Senior Data Engineer - Senior Associate

At EY, we’re all in to shape your future with confidence.   We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. ​   Join EY and help to build a better working world.   Role Overview EY Luxembourg’s Digital Factory is looking for a  Senior Data Engineer - Senior Associate  to help design, build and improve reusable data and platform capabilities across consulting digital solutions. The role will initially support the Questionnaire and Survey Platform, which enables structured questionnaires, survey issuance, evidence collection, workflow tracking, reminders, review, approval and audit history. Over time, the successful candidate may also contribute to other Digital Factory initiatives requiring data modelling, pipeline engineering, integration, automation, auditability and operational reliability. This is a hands-on engineering role suited to a data engineer with solid Python, SQL, data modelling and production engineering experience. Prior exposure to Apache Airflow, graph database technologies or Azure platform services is beneficial, but not mandatory. For an internal hire, these specialised capabilities can be developed through project delivery, coaching and structured learning.   Initial Project Context

The initial project is a reusable questionnaire and evidence collection capability. The platform is intended to support common questionnaire patterns such as template configuration, question management, response capture, evidence upload, workflow status tracking and audit trail generation. The target design may involve workflow orchestration, metadata modelling, SQL-based evidence and audit persistence, and secure API-driven integration with platform and consuming application services. Technologies such as Apache Airflow, graph databases and Azure services may be used where appropriate.

Key Responsibilities Data Engineering and Delivery

Design, build and maintain data pipelines, data services and integration components for Digital Factory solutions. Develop maintainable Python components for data processing, automation, integration and operational workflows. Translate business and platform requirements into reliable technical designs, data models and engineering deliverables. Support reusable platform capabilities that can be adopted across multiple consulting digital solutions.

SQL, Data Modelling and Auditability

Design SQL schemas for operational data, evidence metadata, workflow status history, notification records and audit events. Support auditability, traceability, status history and evidence metadata patterns. Design secure references to documents or object storage, including metadata, versioning, ownership and retention attributes. Support reporting, dashboarding and export needs through reliable data structures.

Workflow, Integration and Operations

Support orchestration patterns for scheduling, reminders, escalations, reporting and controlled reruns. Build integration components for API-driven, asynchronous or event-driven workflows. Implement logging, monitoring, diagnostics, automated tests and data quality checks. Document data models, workflow behaviour, technical decisions, runbooks and support procedures.

Security, Privacy and Governance

Apply secure data handling practices, including access control, encryption, secrets management and least privilege principles. Support expectations around auditability, lineage, retention and evidence generation. Work with project managers, architects, backend engineers, QA, security, privacy and business stakeholders.

Required Qualifications and Experience

Relevant professional experience as a Data Engineer, Platform Engineer, Data-focused Software Engineer or similar technical role. Hands-on experience with Python for pipeline, automation, integration or service development. Strong SQL skills, including schema design,