Senior Data Engineer
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 7+ years
- Category
- Data engineering
- Posted
Skills
Must have
- The strongest candidate will be a senior-level engineer who can take ownership of a complex data environment without requiring significant day-to-day direction. This person should be comfortable movin
- Strong candidates will bring excellent problem-solving skills, attention to data quality and reliability, and the ability to identify and implement improvements rather than simply maintain existing pr
Full description
Senior Data EngineerLocation: North Seattle or Remote, Pacific Time Zone only
About the Opportunity
Seattle Search Group is partnering with a growing organization to identify an experienced Senior Data Engineer to lead the development and ongoing operation of its enterprise data environment.
This is a highly hands-on role combining senior-level data engineering with technical leadership. The Senior Data Engineer will take ownership of critical databases, data warehouses, and cloud-based data pipelines while providing leadership to a small data team.
The environment is heavily Microsoft-focused, including Microsoft Fabric, Azure, Azure DevOps, Power BI, PySpark, Python, and T-SQL.
This position is ideal for someone who enjoys building systems rather than simply maintaining them. The successful candidate will be comfortable working independently, solving complex production issues, improving architecture, and creating reliable data processes that support both business operations and analytics.
Key ResponsibilitiesData Architecture & Engineering
- Design, develop, and maintain scalable enterprise data warehouse solutions using Microsoft Fabric, including Warehouse and Lakehouse environments.
- Build and maintain fact and dimension models supporting operational reporting and analytics.
- Develop structured data environments using Medallion architecture concepts, including Bronze, Silver, and Gold layers.
- Improve data storage, processing performance, query efficiency, and overall platform scalability.
- Establish technical standards and best practices for the organization's data environment.
Data Pipelines & Integration
- Build and maintain ETL/ELT pipelines using PySpark, Python, SQL, and Azure technologies.
- Develop reliable processes for moving and transforming data between multiple business systems.
- Monitor production pipelines and proactively address failures, bottlenecks, and data-quality issues.
- Establish monitoring, alerting, and recovery processes for critical data workflows.
- Troubleshoot issues across ingestion, transformation, database, and storage environments.
Database Engineering
- Develop and optimize advanced T-SQL, including stored procedures, functions, views, and complex queries.
- Perform database and query performance tuning.
- Develop indexing strategies for transactional and analytical workloads.
- Maintain standards around database design, documentation, and naming conventions.