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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # SENIOR DATA ENGINEER - **Company:** US Neuro LLC - **Location:** Fort Worth, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Application Services, Microsoft Azure, Clinical Data Repository, Information Systems, Databases, Computer Literacy, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Structures, Data Systems, Data Warehousing, Database Development, Dimensional Modeling, Document-Oriented Databases, Python (Programming Language), PostgreSQL, Machine Learning, Microsoft SQL Server, Performance Tuning, Power BI, Software Engineering, Systems Architecture, Tableau (Software), Unstructured Data, Data Processing, Google Cloud, Cloud Platform System, Azure Data Factory, Sql Optimization, Snowflake, Apache Spark, Electronic Medical Records, Information Technology, Data Management, Data Delivery, Data Pipelines, Databricks, Programming Languages - **Published:** October 2, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=5acff10101632d23 ## About the Role * Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Mathematics, or a related field. * Equivalent relevant experience may be considered in lieu of education. Experience * Three or more years of experience in data engineering, database development, or a related data management role. * Demonstrated experience building and maintaining production ETL/ELT pipelines. * Experience working with large structured and unstructured datasets. * Experience supporting business intelligence and analytics environments. Technical Skills * Healthcare industry experience. * Knowledge of HIPAA and healthcare data privacy requirements. * Advanced SQL skills and proficiency in Python or a comparable programming language. * Experience with a major cloud platform such as Microsoft Azure, AWS, or Google Cloud. * Knowledge of data warehousing, dimensional modeling, APIs, data integration, and automation frameworks. * Experience with relevant tools such as Azure Data Factory, Databricks, Snowflake, SQL Server, PostgreSQL, Power BI, Tableau, Apache Spark, or Airflow. * Experienced leading a team of 2 or more employees., * Experience supporting EMR/EHR, revenue cycle, billing, claims, provider, or clinical data environments. * Experience with machine learning, AI, or advanced analytics platforms. * Relevant cloud or data engineering certification. Key Competencies * Analytical problem solving * Data governance and quality management * Process improvement and automation * Project planning and execution * Stakeholder communication * Attention to detail * Business acumen * Collaboration and technical leadership Physical and Work Requirements * Prolonged periods of sitting and computer use. * Ability to work effectively in an office, hybrid, or remote environment as assigned. ## Description The Data Engineer is responsible for designing, building, and maintaining scalable data infrastructure that supports business intelligence, analytics, operational reporting, and data-driven decision-making. This role develops and manages data pipelines, integrates multiple data sources, promotes data quality, and collaborates with stakeholders across the organization to deliver reliable data solutions. The ideal candidate combines strong technical expertise with business acumen and can translate operational requirements into efficient, scalable data architecture., Data Architecture and Engineering * Design, develop, and maintain enterprise data pipelines and workflows. * Build and optimize ETL/ELT processes that move data between source systems and data warehouses. * Manage data integration across platforms, databases, APIs, and third-party applications. * Develop and maintain data models that support reporting, analytics, and operational needs. * Implement scalable cloud-based data solutions. Data Quality and Governance * Establish and maintain data validation, cleansing, reconciliation, and monitoring processes. * Identify and resolve data discrepancies, duplicate records, and integrity issues. * Support master data management and source-of-truth initiatives. * Apply organizational data governance, privacy, and security standards. Reporting and Analytics Support * Partner with business leaders, analysts, and operational teams to define reporting requirements. * Deliver trusted datasets and data structures that support dashboards, KPIs, and business intelligence tools. * Optimize data delivery processes to improve reporting accuracy, timeliness, and efficiency. * Support advanced analytics, forecasting, automation, and responsible AI initiatives. Performance Optimization * Monitor and improve database, query, and pipeline performance. * Troubleshoot data processing issues and implement sustainable corrective actions. * Automate manual data collection, validation, and reporting processes. * Identify opportunities to improve reliability, scalability, and cost efficiency. Collaboration and Documentation * Work closely with business stakeholders, developers, analysts, vendors, and leadership. * Document data flows, system architecture, business rules, processes, and standards. * Participate in requirements gathering, project planning, testing, deployment, and change management. * Provide technical guidance and mentoring as appropriate.