As a Data Engineer at Hologic, the business and/or technical problem is to design, develop, and optimize advanced data solutions that enable business intelligence and analytics across the organization, leveraging modern cloud technologies to architect scalable data pipelines, ensure data quality, and deliver actionable insights that support strategic decision-making, thereby advancing Hologic’s data-driven culture and supporting its mission to deliver innovative healthcare solutions.
Requirements
- Demonstrated expertise in Microsoft Azure data services (Data Factory, Data Lake, Synapse Analytics, Databricks, Power BI).
- Hands-on experience with SQL, Python, and PySpark for data engineering and analytics.
- Strong knowledge of data warehousing concepts, relational and dimensional modeling, and modern data architectures.
- Experience integrating data from ERP/CRM systems (e.g., Oracle EBS, Salesforce) and streaming platforms.
- Familiarity with IoT/event hub integrations and advanced analytics platforms.
- Professional certifications in Microsoft Azure, Databricks, or related cloud/data technologies.
- Experience supporting large-scale analytics in healthcare, life sciences, or regulated industries.
Responsibilities
- Design and build data warehouse structures, including fact and dimension tables, to support scalable analytics and reporting solutions.
- Develop, optimize, and manage ETL/ELT processes across diverse data sources (ERP, CRM, IoT, streaming).
- Implement and uphold data governance, security, and compliance standards across environments.
- Contribute to DevOps practices, including CI/CD pipelines, version control, and automated testing.
- Create clear documentation of architectures, workflows, and technical processes.
- Collaborate within Agile teams to iteratively deliver data capabilities and continuous improvements.
- Partner with business and technical teams to translate requirements into secure, high-quality data solutions.
Other
- Proven ability as a seasoned, experienced professional with a full understanding of data engineering and related specializations.
- Skilled at working on problems of diverse scope, applying judgment to select appropriate methods, techniques, and solutions.
- Excellent communication and collaboration skills with the ability to work independently and in cross-functional teams, typically receiving minimal instruction on day-to-day tasks.
- Experience with Agile methodologies, process improvement, and stakeholder engagement.
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field and 5–8 years of professional experience; or Master’s degree with 1–3 years of experience.
