• Design, build, and maintain scalable, high-quality data pipelines supporting both real-time and batch analytics workloads • Develop and optimize ETL/ELT processes using modern cloud data technologies and orchestration tools • Contribute to the design and evolution of lakehouse and warehouse data models that support analytics and reporting needs • Partner with business, design, test, and development teams to understand data requirements and improve data capture strategies • Help lead technical writing initiatives, including goal-setting, planning, and execution • Write, edit, and maintain clear, concise, and well-structured technical documentation • Create and improve documentation standards, organization, and knowledge-sharing processes • Organize and curate documentation to ensure it is intuitive, discoverable, and up to date • Advocate for consistent knowledge sharing across teams and studios • Research and propose improvements to documentation workflows and solutions to existing pain points • Apply modern engineering best practices to ensure reliability, scalability, and data quality across platforms

Role Description As a Data Engineer on the Data Pipeline team, you will build and support modern, large-scale analytics platforms that power data-driven decision-making across the studio. You’ll work hands-on with cloud-based lakehouse and warehouse architectures, designing and maintaining real-time and batch data pipelines that serve business, design, test, and development stakeholders. This role sits at the intersection of data engineering, analytics enablement, and documentation, helping teams not only use data effectively but also understand and trust the systems behind it. You’ll contribute to a culture of test-driven, data-informed development by shaping how data is captured, processed, documented, and shared. Attention to detail, strong engineering fundamentals, and a passion for scalable, modern data architecture are key to success in this role. Responsibilities - Design, build, and maintain scalable, high-quality data pipelines supporting both real-time and batch analytics workloads - Develop and optimize ETL/ELT processes using modern cloud data technologies and orchestration tools - Contribute to the design and evolution of lakehouse and warehouse data models that support analytics and reporting needs - Partner with business, design, test, and development teams to understand data requirements and improve data capture strategies - Help lead technical writing initiatives, including goal-setting, planning, and execution - Write, edit, and maintain clear, concise, and well-structured technical documentation - Create and improve documentation standards, organization, and knowledge-sharing processes - Organize and curate documentation to ensure it is intuitive, discoverable, and up to date - Advocate for consistent knowledge sharing across teams and studios - Research and propose improvements to documentation workflows and solutions to existing pain points - Apply modern engineering best practices to ensure reliability, scalability, and data quality across platforms Qualifications - 5+ years of professional experience working with SQL - 5+ years of experience designing and implementing scalable ETL processes, including data movement and data quality tooling - Hands-on experience with cloud-based data orchestration solutions (e.g., Azure Data Factory or equivalent) - 3+ years of experience with modern big data analytics platforms, including: - Data lakes - Distributed processing frameworks (e.g., Spark) - Columnar storage formats such as Parquet - 2+ years of experience building and supporting cloud-hosted data systems - Strong understanding of data modeling, pipeline reliability, and performance optimization Preferred Qualifications - Experience building data pipelines using cloud-native analytics platforms and services (e.g., data factory tools, analytics warehouses, and Spark-based processing) - Hands-on experience working with Delta Lake and transactional data lake formats - Experience querying and integrating data from high-performance analytics engines (e.g., time-series or log-based systems such as Kusto/Azure Data Explorer) - Exposure to AI/ML-focused data engineering use cases, including: - Feature engineering and feature stores - Model training and serving datasets - Model monitoring and observability pipelines - Experience preparing, governing, and securing datasets for modern AI applications, including: - LLM and RAG workflows - Experimentation and A/B testing - Privacy-aware and compliant data access patterns Salary Range At Blueprint, we strive to offer competitive pay that reflects the value of our team members. Compensation for this role is influenced by a variety of factors, including skills, education, responsibilities, experience, and geographic market. For candidates based in Washington State, the anticipated salary range is $43 to $45.38 USD/Hourly. Please note that we typically do not hire new employees at the top of the posted range. Actual starting pay will be determined based on experience, skills, and internal equity. The final salary and job title may vary depending on the selected candidate’s qualifications and could fall outside the stated range. Benefits - Medical, dental, and vision coverage - Flexible Spending Account - 401k program - Competitive PTO offerings - Parental Leave - Opportunities for professional growth and development Equal Opportunity Employer Blueprint Technologies, LLC is an equal employment opportunity employer. Qualified applicants are considered without regard to race, color, age, disability, sex, gender identity or expression, orientation, veteran/military status, religion, national origin, ancestry, marital, or familial status, genetic information, citizenship, or any other status protected by law. If you need assistance or a reasonable accommodation to complete the application process, please reach out to: recruiting@bpcs.com Location Remote

• Design, configure, and implement data replication between SAP HCM and other SAP systems (e.g., SuccessFactors, EC Payroll, SAP S/4HANA) • Develop and maintain integration interfaces using SAP CPI, including iFlows, adapters, and mappings • Implement, configure, and support both BIB (Business Integration Builder) and PTP (Point to Point) replication scenarios • Lead and execute data migration and transformation activities for legacy-to-SAP and SAP-to-SAP HCM transitions • Lead work in collaborating with other project team members on necessary data transformations to/from SAP SuccessFactors necessary for replication and data migration scenarios • Analyze, map, and transform data between source and target systems ensuring accuracy, consistency, and completeness • Work with stakeholders to understand functional requirements and translate them into scalable technical solutions for the project lifecycle as related to both replications and data • Perform data validation, testing, and quality assurance in coordination with functional teams • Provide integration and data support during cutover, go-live, and post-production phases • Work with other project team members to execute cutover items related to data, replications, and migration per project phase. Including project planning with the project managers • Document integration architecture, interface designs, and migration plans • Ensure compliance with SAP best practices, security standards, and data governance policies

• Diseñar, desarrollar y mantener pipelines de datos robustos y escalables • Integrar fuentes de datos heterogéneas y garantizar la calidad de la información • Colaborar con equipos de analytics y producto para entender necesidades de datos • Optimizar procesos de ingesta, transformación y almacenamiento de datos • Documentar arquitecturas y procesos de datos