Gravity IT Resources
Role: Azure Data Engineer
Work Authorization: USC/GH Holder
Referral Fee: +/- $1000
Opportunity for Impact
The Data Engineer will be a key member of the Data & Analytics team and will play a critical role in building a leading-edge Data & Analytics platform for enabling value-based healthcare, population health management, and enterprise analytics. This role will have frequent interactions with the clinical and administrative stakeholders in the healthcare organization. As a data engineer, this person will design, develop, maintain, and support the cloud-based (Microsoft Azure) big data platform and will use modern data engineering design patterns and tools.
- Design, build and maintain scalable, automated data pipelines to enable Reporting, Data Visualization, Advanced Analytics, Data Science, and Machine Learning solutions.
- Support critical data pipelines with a scalable distributed architecture, including data ingestion (streaming, events, and batch), data integration (ETL, ELT, Azure Data Factory), and distributed data processing using Databricks Data & Analytics and Azure Cloud Technology Stacks.
- Build cloud data solutions using multiple technologies, such as SQL, Python, Data Lake (Databricks Delta Lake), Cloud Data Warehouse (Azure Synapse), RDBMS, NoSQL databases.
- Understand and implement best practices in managing data, including master data, reference data, metadata, data quality, and lineage.
- Deploy, automate, maintain, and manage cloud-based production systems to ensure the availability, performance, scalability, and security of production systems.
- Engage with cross-functional stakeholders to identify pain points, business & technical requirements, and to design data solutions using best-practice patterns and modern architecture.
- Own end-to-end design and development, testing, the release of critical components using Databricks technology stack and Microsoft Azure cloud platforms and services.
- BA or BS degree in Computer Science, Information Systems, or related field required. MS in Business Analytics or related discipline preferred.
- 3-5 years of experience in creating robust enterprise-grade data engineering pipelines using SQL, Python, Apache Spark, ETL, ELT, Databricks Technology Stack, Azure Cloud Services, Cloud-based Data & Analytics platforms.
- Experience in distributed data (structured, semi-structured, unstructured, streaming) processing techniques using Apache Spark, Hadoop, Hive, Kafka, and big data ecosystem technologies.
- Experience in data modeling and design for data warehouse, relational databases, and NoSQL data stores. Strong proficiency in SQL and data analysis required.
- Familiarity with Data Science and Machine Learning technologies, development process, and common Machine Learning libraries (e.g., Scikit-Learn, Tensorflow).
- Strong problem-solving, critical thinking, verbal, and written communication skills.
- Ability to influence decisions related to advanced analytics strategy & roadmaps, business use cases, and data platform capabilities.
- Effective communication and collaboration with internal cross functional teams, leadership team, technology partners & vendors, and end users.
- Excellent analytical, organizational skills and ability to work in a startup environment and to deliver on tight deadlines using Agile practices.
- Healthcare industry experience highly desired.