Data Engineer

• Design, develop, and optimize advanced data solutions that enable business intelligence and analytics across the organization. • Leveraging modern cloud technologies, you will architect scalable data pipelines, ensure data quality, and deliver actionable insights that support strategic decision-making. • 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). • Partner with business and technical teams to translate requirements into secure, high-quality data solutions. • 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 architecture, workflows, and technical processes. • Collaborate within Agile teams to iteratively deliver data capabilities and continuous improvements. Requirements Technical Skills: • Proven ability as a seasoned, experienced professional with a full understanding of data engineering and related specializations. • 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 architecture. • Experience integrating data from ERP/CRM systems (e.g., Oracle EBS, Salesforce) and streaming platforms. • Skilled at working on problems of diverse scope, applying judgment to select appropriate methods, techniques, and solutions. Soft Skills: • Strong problem-solving and analytical skills. • Attention to detail and a commitment to quality • 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. Skills, Specialized Knowledge (Desired): • Experience supporting large-scale analytics in healthcare, life sciences, or regulated industries. • Familiarity with IoT/event hub integrations and advanced analytics platforms. • Experience with Agile methodologies, process improvement, and stakeholder engagement. Education: • Professional certifications in Microsoft Azure, Databricks, or related cloud/data technologies. • Bachelor's degree in computer science, Information Technology, or a related field (or equivalent experience). Experience: • At least 3 years’ experience: Proven hands-on experience in a data engineering professional.