Data Engineer

Job Description

Job Description

We are looking for an experienced Data Engineer to join our dynamic team in Wyoming, Michigan, for a Contract-to-Permanent position. In this role, you will play a key part in designing and managing data systems, developing data pipelines, and ensuring optimal data governance practices across multi-cloud environments. This position offers an exciting opportunity to contribute to cutting-edge healthcare data solutions while collaborating with cross-functional teams.

Responsibilities :

• Design and implement robust data architecture frameworks, including modeling, metadata management, and database security.
• Create and maintain scalable data models that support both operational and analytical needs.
• Develop and manage data pipelines to extract, transform, and load data from diverse sources into a centralized data warehouse.
• Collaborate with various departments to translate business requirements into technical specifications.
• Monitor and optimize the performance of data assets, ensuring reliability and efficiency.
• Implement and enforce data governance policies, including data retention, backup, and security protocols.
• Stay updated on emerging technologies in data engineering, such as AI tools and cloud-based solutions, and integrate them into existing systems.
• Establish and track key performance indicators (KPIs) to measure the effectiveness of data systems.
• Provide mentorship and technical guidance to team members to foster a collaborative work environment.
• Evaluate and adopt new tools and technologies to enhance data capabilities and streamline processes.
• Proficiency in managing both NoSQL and Graph databases in multi-cloud environments, such as AWS Neptune, Apache Gremlin, Neo4J, and Azure Cosmos.
• Strong expertise in relational databases like Snowflake, Azure Data Factory, or similar technologies.
• Experience building and maintaining data pipelines using tools like PowerShell, Python, or ETL processes.
• Advanced knowledge of data architecture principles, including database modeling and design.
• Familiarity with big data tools such as Apache Spark, Hadoop, and Kafka.
• Hands-on experience with cloud platforms including Amazon Web Services (AWS) and Microsoft Azure.
• Solid understanding of Agile methodologies and their application in data engineering projects.
• Exceptional analytical and problem-solving skills to address complex data challenges.