Senior Data Engineer (Databricks)

Status: Direct Hire

Job Title: Sr. Data Engineer

Location: Remote

Salary: $55-$60/hr

About the company:

We are a highly experienced team of architects, interface designers, and engineers who assist our clients with transforming data into beneficial information, delivering collaborative web experiences, and building custom business applications.

Our elegant software and data solutions help clients educate kids, transform healthcare, clean the environment, promote energy efficiency, and encourage healthy lifestyles. Organizations of all sizes like Nike, Northwest Energy Efficiency Alliance, Cambia Health, and the Beaverton School District rely on us.

Here it’s all about our people. We pride ourselves on hiring brilliant, empathetic, lifelong learners who bring the best results; reducing project risk and maximizing project success. We embrace agnostic solutions, knowing the right answer doesn’t always come from a single source. Because we architect from a diverse portfolio of modern technologies, we can ensure the delivery of innovative solutions our clients can successfully support and extend.

Beginning with the end customer, we apply a user-centered approach. Our seasoned team invests to understand the business problem, then creates sustainable, performant, and scalable architectures that are perfectly suited for their application.

Senior Data Engineer (Databricks):

Our client is seeking a Senior Data Engineer to join a growing data engineering team focused on building modern, cloud-based data platforms that drive enterprise analytics, reporting, and operational decision-making. This role is ideal for a highly skilled Databricks professional who enjoys designing scalable data solutions, solving complex integration challenges, and partnering with both technical and business stakeholders to deliver impactful results. The successful candidate will play a key role in developing robust data architectures, optimizing data pipelines, and helping shape the future of enterprise data capabilities.

This is a remote role with possibility of a changing work model dependent on project needs.

Senior Data Engineer Responsibilities:

• Design, develop, and support modern cloud-based data platforms, including data lakes, data warehouses, and lakehouse environments.
• Build and maintain enterprise-grade data engineering solutions utilizing Databricks, PySpark, Delta Lake, and related technologies.
• Develop scalable ETL/ELT pipelines that ingest, transform, validate, and deliver data from a variety of enterprise systems and external sources.
• Create and maintain Bronze, Silver, and Gold data layers to support analytics, reporting, and downstream business applications.
• Design logical, physical, and dimensional data models that enable efficient data consumption and reporting.
• Integrate data from ERP systems, operational platforms, APIs, databases, flat files, and third-party applications.
• Develop and support REST API integrations and data services that facilitate data exchange across enterprise systems.
• Partner with business analysts, architects, data consumers, and leadership teams to gather requirements and deliver data-driven solutions.
• Implement monitoring, alerting, and observability practices to ensure reliability and performance of production data pipelines.
• Troubleshoot and resolve data quality, integration, and performance issues across complex environments.
• Optimize data processing frameworks and cloud resources for scalability, efficiency, and cost management.
• Contribute to data architecture discussions, technical standards, and engineering best practices.
• Provide technical leadership, mentorship, and guidance to team members as needed.
• Support the continuous improvement of data engineering processes, tools, and development methodologies.

Senior Data Engineer Qualifications:

• 5+ years of experience in Data Engineering, Data Platform Development, Software Engineering, or a related technical field.
• Expert-level experience with Databricks, including PySpark, Delta Lake, Databricks Workflows, and Lakehouse Architecture.
• Strong hands-on programming experience with Python and advanced SQL development.
• Proven experience designing, building, and supporting large-scale ETL/ELT pipelines in production environments.
• Experience developing cloud-based data solutions within Azure and/or AWS environments.
• Strong understanding of modern data warehousing, data lake, and lakehouse design principles.
• Experience working with structured, semi-structured, and large-scale enterprise data sets.
• Hands-on experience with relational database platforms such as SQL Server, PostgreSQL, Oracle, MySQL, DB2, or similar technologies.
• Experience integrating data from enterprise applications, financial systems, ERP platforms, and external data sources.
• Knowledge of API-based integrations and data exchange methodologies.
• Experience implementing data quality, governance, monitoring, and performance optimization strategies.
• Familiarity with workflow orchestration and automation tools such as Airflow, Prefect, Dagster, or similar platforms.
• Experience supporting business intelligence and analytics initiatives through delivery of curated, analytics-ready datasets.
• Understanding of distributed data platforms, NoSQL databases, or big data technologies is preferred.
• Experience with Microsoft Fabric, Power BI integration, streaming data platforms, CI/CD practices, or modern DevOps methodologies is a plus.
• Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
• Demonstrated ability to work independently, manage competing priorities, and thrive in evolving project environments.