Job Opportunities API

Driven by the passion to improve quality of people’s lives, WSA continues to grow as market leader in the hearing aid industry. With our commitment to increase penetration in an underserved hearing care market, we want to accelerate our business transformation in order to reach more people, more effectively. We're looking for a Lead Data Engineer to define the technical direction of our Azure data platform while remaining hands-on in engineering delivery. You'll drive platform architecture, establish engineering standards, mentor Data Engineers, and deliver scalable, governed, and AI-ready data products that enable trusted business insights. What you will do You will join the Data Platform & Products Team and serve as the senior technical authority for data platform architecture, data modelling, and engineering standards. Define and own the data platform architecture Define and maintain the enterprise data platform architecture and roadmap, ensuring it supports current analytics needs and scales toward future AI/ML use cases. Design scalable Lakehouse architectures using Azure Data Lake Storage, Databricks, and Delta Lake — including Medallion Architecture layer definitions (Bronze, Silver, Gold) and inter-layer data contracts. Establish architecture standards, design patterns, and engineering best practices that guide the entire team's technical decisions. Drive technology evaluation, platform evolution decisions, and architectural trade-off analysis with clear documentation of rationale. Design, own, and maintain data products Own the full lifecycle of data products across multiple mobile app brands — from initial design and development through release, ongoing maintenance, schema evolution, and eventual deprecation. Design conceptual, logical, and physical data models that reflect the business domains of each brand application, ensuring data products remain accurate and fit for purpose as source apps evolve. Define reusable data product standards and frameworks — including schema conventions, SLA definitions, certification tiers, versioning policies, and ownership models — that apply consistently across all products in the portfolio. Establish business data domain boundaries and stewardship models, ensuring each data product has a clear owner, defined consumers, and documented change management processes. Guide creation and continuous improvement of Gold layer datasets that serve as the single source of truth for analytics, reporting, and compliance use cases across the organisation. Coordinate cross-product dependencies — identifying where data products from different mobile apps share dimensions, metrics, or regulatory requirements, and designing shared models that reduce duplication and increase consistency. Lead hands-on engineering delivery Develop reference implementations and reusable pipeline frameworks that Data Engineers can build upon. Build and directly support critical data ingestion and transformation pipelines where architectural complexity demands it. Conduct design reviews and code reviews to ensure implementations conform to platform standards and do not introduce technical debt. Collaborate closely with Data Engineers on implementation challenges, troubleshooting, and performance optimisation. Govern data and ensure compliance Establish data governance standards, metadata practices, and data lifecycle policies across the platform. Define data contracts and schema management processes that govern how data is produced, versioned, and consumed. Ensure the platform aligns with privacy, security, and regulatory requirements — including GDPR and any industry-specific compliance obligations. Partner with Microsoft Purview or equivalent tooling to implement data cataloguing, lineage tracking, and classification at scale. Prepare the platform for AI/ML and advanced analytics Define architecture patterns that support advanced