Job description

ROLE SUMMARY The Azure Data Analytics Engineer will be the AZURE SME tasked with the development and optimization of cloud-based Business Intelligence solutions. Advances data analytics capabilities and drives innovative solutions. Possesses deep technical expertise in data engineering and plays instrumental role in managing data integrations from on-premises Oracle systems, Cloud CRM (Dynamics), and telematics. Collaborates closely with Data Science and Enterprise Data Warehouse teams and business stakeholders. This is an on-site position based in NJ. PRIMARY RESPONSIBILITIES: Data Ingestion and Storage: • Designs, develops, and maintains scalable, efficient data pipelines using Data Factory, and Databricks, leveraging Py Spark for complex data transformations and large-scale processing. • Builds and manages extract, transform, and load (ETL)/extract, load, transform (ELT) processes to seamlessly extract, transform, and load data from on-premises Oracle systems, customer relationship management (CRM) technology, and connected vehicles into data storage solutions, such as Azure Data Lake Storage and Azure SQL Database. Data Engineering: • Creates high-code data engineering solutions using Databricks to clean, transform, and prepare data for in-depth analysis. • Develops and manages data models, schemas, and data warehouses, utilizing Lakehouse Architecture to enhance advanced analytics and business intelligence. • Leverages Unity Catalog to ensure unified data governance and management across the enterprise's data assets. • Optimizes data storage, retrieval strategies, and query performance to drive scalability and efficiency in all data operations. Data Integration: • Integrate and harmonize data from diverse sources including on-premises databases, cloud services, APIs, and connected vehicle telematics. • Ensure consistent data quality, accuracy, and reliability across all integrated data sources. GitHub Development: • Utilizes GitHub for version control and collaborative development, implementing best practices for code management, testing, and deployment. • Develops workflows for continuous integration (CI) and continuous deployment (CD), ensuring efficient delivery and maintenance of data solutions. ADDITIONAL RESPONSIBILITIES: • Work closely with Data Science, Enterprise Data Warehouse, and Data Visualization teams, as well as business stakeholders, to understand data requirements and deliver innovative solutions. • Collaborate with cross-functional teams to troubleshoot and resolve data infrastructure issues, identifying and addressing performance bottlenecks. • Provide technical leadership, mentorship, and guidance to junior data engineers, promoting a culture of continuous improvement and innovation. REQUIRED SKILLS AND PERSONAL QUALIFICATIONS: • Technical Expertise: Extensive experience with Azure Data Factory, Databricks, and Azure Synapse, as well as proficiency in Python and PySpark. • Data Integration: Experience integrating data from on-premises Oracle systems and connected vehicle data into cloud-based solutions. • Lakehouse Architecture & Governance: Deep knowledge of Lakehouse Architecture and Unity Catalog for enterprise data governance. • Version Control & Collaboration: Demonstrated proficiency in GitHub for development, collaboration, and deployment in large-scale environments. • Infrastructure as Code (IaC): Experience with Infrastructure as Code tools such as Resource Manager (ARM) templates or terraform. • Problem-Solving & Troubleshooting: Strong analytical skills with the ability to diagnose and resolve complex data infrastructure challenges. • Collaboration: Proven ability to work effectively with Data Science teams, business stakeholders, and cross-functional teams to drive data-driven insights. • Communication: Excellent verbal and written communication skills with the ability to translate technical concepts to non-technical stakeholders. Education/Experience Requirements: BA/BS with 4 to 6 years of relevant experience. Relevant experience accepted in lieu of a degree. Work Environment • Hybrid Role: Remote work 2 days per week (After 90 Days Onboarding) • Travel Required: 0%

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