Data Engineer - Remote w2

Title: Data Engineer Location: REMOTE -- Still need candidates in these cities but they should only expect to go onsite 2-3x per month Dallas/Frisco, Tampa/ FTL, NYC, Louisville, Chicago, ATL, Boston, Nashville, Charlotte (expect to go onsite 2-3x per month) Duration: 12+ Months Contract to hire Interview Mode: Video Job Description Position Overview They need AI experience along with all the must haves Client is seeking a Data Engineer to support enterprise data and analytics initiatives by designing, developing, and maintaining scalable data pipelines and solutions. This individual will work closely with business stakeholders, data analysts, data scientists, and technology teams to ensure high-quality, accessible data that supports reporting, analytics, and operational decision-making across the organization. Key Responsibilities • Design, develop, and maintain scalable ETL/ELT data pipelines. • Build and optimize data integration processes from multiple internal and external sources. • Develop and support data models, data warehouses, and data lake environments. • Ensure data quality, integrity, consistency, and governance standards are met. • Collaborate with business and technical teams to translate requirements into data solutions. • Monitor and troubleshoot data workflows and production issues. • Optimize database performance, query efficiency, and data processing jobs. • Support analytics, reporting, machine learning, and business intelligence initiatives. • Create and maintain technical documentation and data lineage processes. • Participate in Agile development activities, including sprint planning and backlog grooming. Required Qualifications • Bachelor's degree in Computer Science, Information Systems, Engineering, or related field. • 5+ years of experience in Data Engineering or related data development roles. • Strong experience with SQL and relational databases. • Hands-on experience developing ETL/ELT processes. • Experience with cloud data platforms such as Azure, AWS, or Google Cloud. • Proficiency with Python, Spark, or other data processing technologies. • Experience working with large-scale structured and unstructured datasets. • Understanding of data warehousing concepts and dimensional modeling. • Knowledge of data governance, security, and compliance best practices. • Strong analytical, problem-solving, and communication skills. Preferred Qualifications • Healthcare or payer industry experience. • Experience supporting Medicare, Medicaid, or healthcare analytics initiatives. • Familiarity with Azure Data Factory, Databricks, Synapse, Snowflake, Hadoop, or similar technologies. • Experience with Power BI, Tableau, or other BI/reporting tools. • Exposure to machine learning and advanced analytics environments. • Experience working in highly regulated healthcare environments. Notes • Designs, builds, and maintains scalable data processing solutions and data pipelines • Works with structured and unstructured data to support analytics and business insights • Uses cloud-native technologies and engineering best practices • Specifically mentions: • Azure Databricks • Large-scale data pipeline development and optimization