À propos de ce poste Data Engineer chez Blueprint Technologies
About Blueprint
Blueprint is a technology solutions firm headquartered in Bellevue, Washington, with teams across the United States. We help organizations turn complex challenges into meaningful outcomes by connecting strategy and execution across AI, cloud, data, product development, and emerging technology.
Our culture is built by people who care deeply about doing exceptional work. We set high standards, take ownership, and continually challenge ourselves and one another to be better. We work hard, support each other, and take genuine pride in what we deliver for our clients, partners, and teams.
At Blueprint, you’ll work alongside talented people with different experiences, expertise, and perspectives. You’ll have opportunities to take on meaningful challenges, expand your skills, and see the impact of what you build.
Bring your perspective. Raise the standard. Build what matters.
You will design, develop, and maintain data-intensive systems that support complex data migration, data engineering, and data architecture initiatives. You will focus on building reliable data solutions, improving data quality, and ensuring the accuracy and consistency of data across systems. Using Python, SQL, and Apache Spark, you will develop data processing workflows, perform data validation and reconciliation, troubleshoot technical issues, and support the delivery of high-quality data products. Your work will contribute to efforts addressing cybercrime and supporting lawful access requests through secure, reliable, and well-engineered data systems.
- Design, develop, and maintain scalable data engineering solutions to support data migration, processing, and integration initiatives.
- Build and optimize data pipelines and processing workflows using Python, SQL, and Apache Spark.
- Perform data quality assessments, validation, reconciliation, and comparisons to ensure data accuracy, completeness, consistency, and integrity.
- Analyze business and system requirements and translate them into technical specifications and reliable data solutions.
- Develop, test, and maintain data transformation logic and software components to support new and existing systems.
- Troubleshoot complex data processing issues, investigate discrepancies, identify root causes, and implement corrective actions.
- Prepare technical documentation, test plans, and validation procedures for data migration and engineering projects.
- Conduct unit testing, integration testing, and quality assurance reviews to verify the accuracy and reliability of developed solutions.
- Support data migration activities, including data mapping, transformation, validation, and post-migration verification.
- Collaborate with engineering and cross-functional stakeholders to resolve technical challenges and deliver solutions within established timelines.
- Optimize data processing performance, maintainability, and reliability across large-scale data systems.
- Bachelor’s degree in Computer Science, Computer Engineering, Data Engineering, or a related technical field.
- 5–7 years of relevant experience in software engineering, data engineering, or data-intensive systems development.
- Strong programming proficiency in Python and SQL.
- Hands-on experience with Apache Spark for large-scale data processing and transformation.
- Experience performing data quality checks, data comparisons, reconciliation, and validation across systems or datasets.
- Strong foundation in computer science fundamentals, including data structures, algorithms, software design, and problem-solving.
- Experience designing, developing, testing, and maintaining complex software or data processing systems.
- Demonstrated ability to troubleshoot production issues, diagnose data discrepancies, and implement effective resolutions.
- Experience with unit testing, test data preparation, and quality assurance for new and existing systems.
- Ability to analyze technical requirements, document specifications, and deliver high-quality solutions within defined timelines.
- Strong analytical, communication, and collaboration skills.
- Experience supporting end-to-end data migration projects, including source-to-target mapping, transformation, reconciliation, and validation.
- Knowledge of data architecture principles, data modeling, and the design of reliable data-intensive systems.
- Experience building, maintaining, and optimizing scalable data pipelines and distributed processing workflows.
- Familiarity with data governance, data integrity controls, and repeatable data quality frameworks.
- Experience working with large or complex datasets across multiple systems and data sources.
- Knowledge of secure data handling practices and systems supporting cybersecurity, digital investigations, or lawful data access processes.
- Experience supporting legacy system modernization, system enhancements, and production deployments.
- Ability to identify opportunities to improve data processing efficiency, system reliability, and data quality through automation.
Benefits
Blueprint believes that healthy, supported employees do their best work. Eligible employees have access to a comprehensive benefits package that may include:
- Medical, dental, and vision coverage
- Flexible Spending Account (FSA)
- 401(k) retirement plan
- Competitive paid time off
- Parental leave
- Professional growth and development opportunities
Benefits and eligibility may vary based on role, employment status, and location.
Equal Employment Opportunity
Blueprint Technologies, LLC is an equal opportunity employer. We consider qualified applicants without regard to race, color, religion, sex, pregnancy, childbirth or related medical conditions, sexual orientation, gender identity or expression, national origin, ancestry, age, disability, genetic information, marital or familial status, military or veteran status, citizenship status, or any other characteristic protected by applicable law.
Applicant Accommodations
If you need a reasonable accommodation to participate in any part of the application or interview process, please contact [email protected].
