Role Description As a Data Analytics & Business Intelligence professional, you will play a key role in transforming complex operational and technical data into trusted, actionable insights that drive performance, improve decision-making, and enhance organizational efficiency. Working cross-functionally with engineering, operations, program management, and business stakeholders, you will be responsible for ensuring data quality and integrity, developing scalable reporting solutions, automating manual processes, and creating dashboards that provide visibility into critical business and operational outcomes. This role is ideal for someone who enjoys solving data challenges, identifying trends and opportunities, and leveraging analytics to support continuous improvement in a fast-paced, mission-critical environment. Responsibilities - Partner with engineering, operations, program management, and business stakeholders to understand objectives, define reporting requirements, and deliver analytics solutions that support informed decision-making. - Analyze large, complex datasets to identify trends, anomalies, performance gaps, risks, and opportunities for operational improvement. - Conduct data quality assessments, validation, and verification activities to ensure accuracy, completeness, consistency, and integrity across multiple data sources. - Design, implement, automate, and maintain scalable data collection, transformation, validation, and reporting processes. - Develop and maintain dashboards, KPI scorecards, reports, and self-service analytics solutions that provide visibility into operational performance, program health, technical metrics, and business outcomes. - Build data validation frameworks, monitoring processes, and quality controls to proactively identify and resolve data issues. - Collaborate with technical teams to enhance data models, reporting structures, metadata management practices, and overall data governance initiatives. - Translate complex technical findings into clear, concise, and actionable recommendations for both technical and executive audiences. - Drive process improvements through automation, standardization, and implementation of scalable analytics and reporting solutions. - Support root cause investigations by leveraging data to identify drivers of operational issues, risks, and performance challenges. - Document methodologies, business requirements, reporting processes, and data quality standards to ensure consistency and scalability. Qualifications - Bachelor's degree in Computer Science, Computer Engineering, Information Systems, Data Analytics, or a related technical field. - 5–7 years of professional experience in data analytics, business intelligence, reporting, data quality management, or a related discipline. - 4+ years of experience conducting data quality validation and verification to ensure data accuracy, completeness, and consistency across multiple systems and sources. - 4+ years of experience analyzing large datasets to identify trends, anomalies, risks, gaps, and opportunities for improvement. - 3+ years of experience developing dashboards, reports, and visualizations using Power BI, Tableau, or similar business intelligence platforms. - Experience designing and implementing data quality monitoring, validation, and governance processes. - Experience automating manual workflows using scripting, workflow automation, or data integration technologies. - Strong analytical, troubleshooting, problem-solving, and investigative skills. - Excellent written and verbal communication skills with the ability to present complex findings to both technical and non-technical audiences. - Demonstrated success delivering scalable solutions that improve operational visibility, efficiency, and data reliability. Preferred Qualifications - Experience working with telemetry, operational, engineering, IoT, industrial controls, critical infrastructure, or comparable technical data environments. - Experience implementing automated data validation, exception management, and monitoring processes. - Experience developing executive-level dashboards, KPI scorecards, and performance reporting frameworks. - Experience supporting mission-critical operational environments where data quality and reliability are essential. - Familiarity with data governance, metadata management, and enterprise reporting best practices. - Experience partnering with cross-functional technical and business teams to drive data-informed decision-making. 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 $135,000–$145,000 USD/Annually. 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

• Play a critical role in developing, maintaining, and scaling the pipelines and data systems that power the client's unified data platform. • Design and maintain robust, scalable ETL/ELT pipelines to ingest and process third-party and first-party datasets. • Apply transformation, normalization, and enrichment rules to ensure data consistency and usability. • Work with product managers, data architects, and content experts to align data structure with business needs. • Support the implementation of data matching and entity resolution processes using AI/ML tools and proprietary frameworks. • Build alerts, logs, and metrics to ensure data flows remain healthy and issues are identified and resolved quickly. • Build and maintain data pipelines using dbt, developing models from raw data through staging and intermediate layers up to final semantic models for use in analytics and dashboards. • Contribute to documentation, code quality standards, and internal best practices to ensure maintainability.

Role Description As a Senior Data Engineer (Microsoft Fabric), you will be a hands-on builder — designing and implementing data pipelines, analytic data products, and platform infrastructure while serving as a trusted technical resource for the client. Strong client-facing skills and the ability to mentor are as important as technical depth. - Build and maintain data pipelines, lakehouses, and semantic models in Microsoft Fabric (Lakehouses, Warehouses, Dataflows Gen2, Data Pipelines, Notebooks). - Implement ELT/ETL patterns using the medallion architecture (bronze/silver/gold) on OneLake. - Manage CI/CD pipelines in Azure DevOps, including Fabric workspace deployment and Git integration. - Write clean, performant SQL (T-SQL) and Python/PySpark for data transformation and engineering. - Collaborate with business stakeholders to translate analytics requirements into data products. - Mentor and teach client team members — you should be comfortable being the expert in the room. - Support migration from legacy reporting tools to Fabric-based solutions. Qualifications - Bachelor's Degree in Computer Science, Engineering, or a related field. - Hands-on experience building in Microsoft Fabric — lakehouses, pipelines, notebooks, Direct Lake/Power BI integration. - Strong Azure ecosystem background: Azure Data Lake Storage Gen2, Azure Data Factory, Entra ID, Azure DevOps. - Proficiency in T-SQL and Python/PySpark; Delta Lake/Parquet format experience. - Experience managing CI/CD for data workloads (Azure DevOps pipelines, Fabric Git integration). - Comfort with dimensional and medallion data modeling. - Advanced English Level is required for this role, as you will work with US clients. Effective communication in English is essential to deliver the best solutions to our clients and expand your horizons. Benefits - Competitive USD salary. - 100% remote work: While you can work from anywhere, you’re always welcome to connect with teammates and grow your network at our coworking spaces across LATAM. - Paid off & national holidays: Take the time you need according to your country’s regulations while receiving your full salary. - Sick leave: Focus on your health without stress. Take the necessary time to recover and feel better. - Annual credit: Spend it on the perks you love to enhance your work-life balance. - Team-building activities: Join us for coffee breaks, tech talks, and after-work gatherings to bond with your Nortal family and feel part of our vibrant community. - Birthday off: Enjoy an extra day off during your birthday week to celebrate in style with friends and family.

• Develop, deploy, and maintain data pipelines and data governance systems on Databricks (Unity Catalog, Delta Lake, Workflows) • Conduct in-depth data analysis, profiling, and processing to classify data by domain and detect personal data (PII) • Contribute to the design of data access systems, focusing on data contracts, catalog access, and grant/rollback automation managed as Infrastructure-as-Code with Terraform • Review access architectures and contracts to ensure flexibility and reusability • Ensure that data products and access controls are deployed according to contracts and operate without unintended side effects • Maintain documentation for data contracts, access models, and governance processes • Monitor and support deployed pipelines and quality checks to ensure they meet data quality and performance expectations • Actively seek out information and internal solutions to ensure reusability and adoption of common data platform technologies