Senior Data Engineer (Databricks & Cloud Analytics

Location: Salt Lake City, UT Salary: $60.00 USD Hourly - $65.00 USD Hourly Description:
About the Role
We are seeking an experienced Senior Data Engineer to design, develop, and support enterprise-scale data solutions that enable analytics, reporting, and business decision-making. In this role, you will collaborate with solution architects, business analysts, data scientists, and stakeholders to build scalable cloud-based data platforms and high-performance data pipelines using modern data engineering technologies. The position requires expertise in Databricks, Apache Spark, cloud analytics platforms, and enterprise data integration within an Agile development environment.

Responsibilities

• Design, develop, test, deploy, and maintain enterprise data engineering solutions using cloud and big data technologies.
• Design and implement scalable ETL/ELT pipelines utilizing Databricks, Apache Spark (PySpark), Delta Lake, and Azure Data Factory.
• Build and maintain high-performance data ingestion, transformation, and integration frameworks for analytics and reporting.
• Develop, optimize, and maintain complex SQL queries, stored procedures, and data transformation processes.
• Design and implement scalable data models supporting business intelligence, analytics, and AI initiatives.
• Build and integrate RESTful APIs, event-driven architectures, and SOAP-based services to support enterprise data exchange.
• Develop and maintain streaming and messaging solutions using Apache Kafka.
• Monitor, troubleshoot, and optimize production data pipelines, perform root cause analysis, and implement long-term solutions.
• Apply data quality, governance, security, and performance best practices across data platforms.
• Manage source code using Git and follow CI/CD and DevOps practices.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Participate in Agile ceremonies including sprint planning, backlog refinement, architecture discussions, code reviews, and retrospectives.
• Create technical documentation, deployment artifacts, testing documentation, and operational runbooks.
• Mentor junior engineers and contribute to engineering standards, best practices, and continuous improvement initiatives.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical discipline, or equivalent professional experience.
• 6+ years of experience designing, developing, and supporting enterprise data platforms, cloud analytics solutions, or large-scale data engineering initiatives.
• Strong hands-on experience with:
• Databricks, Apache Spark (PySpark), Python, SQL, Scala

• Experience with the Databricks ecosystem, including:
• Databricks Workspaces, Delta Lake, Unity Catalog, Delta Live Tables (DLT), Databricks SQL, MLflow, Databricks Jobs

• Strong SQL development skills, including query optimization and performance tuning.
• Experience designing and implementing ETL/ELT solutions using Azure Data Factory or similar cloud integration platforms.
• Experience with Apache Kafka or other event streaming technologies.
• Experience integrating enterprise applications using REST APIs, JSON, XML, and SOAP web services.
• Experience with Azure Data Lake Storage (ADLS Gen2) or comparable cloud storage platforms.
• Experience using Git for source code management and collaborative software development.
• Experience working in Linux environments, including shell scripting and command-line utilities.
• Strong analytical, troubleshooting, and problem-solving skills.
• Experience working in Agile environments utilizing Scrum, Kanban, or SAFe methodologies.
• Demonstrated ability to manage multiple priorities while delivering high-quality solutions.
• Proven ability to work independently while mentoring team members and contributing to technical leadership.
• Ability to communicate complex technical concepts to both technical and non-technical audiences.
• Ability to collaborate effectively with cross-functional teams and stakeholders.

Preferred Skills

• Infrastructure as Code (IaC) tools such as Terraform.
• CI/CD pipeline implementation using Azure DevOps, GitHub Actions, or similar platforms.
• Microsoft Azure cloud services.
• Azure Synapse Analytics.
• Microsoft Fabric.
• Power BI.
• Data governance and metadata management.
• DataOps and MLOps practices.
• Enterprise data warehousing.
• Master Data Management (MDM).
• Experience working with financial services or public sector data environments.

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