• Design, develop, and maintain scalable ETL/ELT pipelines to support enterprise data integration and analytics. • Ingest, transform, and integrate data from diverse sources, including flat files, JSON, XML, Excel, REST APIs, graph databases, and other structured and unstructured data formats. • Develop and optimize SQL and Python-based data processing solutions to support efficient data ingestion and transformation. • Build and maintain reusable, scalable data workflows that support business intelligence, reporting, and advanced analytics. • Load, manage, and optimize data within modern data platforms, including Databricks Unity Catalog and SQL Server Managed Instances. • Support both batch and streaming data ingestion frameworks. • Implement and maintain modern Lakehouse architecture solutions to improve scalability, performance, and accessibility. • Monitor and optimize database and pipeline performance to ensure efficient processing and storage. • Implement data quality controls to ensure the accuracy, consistency, reliability, and integrity of enterprise data. • Maintain data lineage and metadata to support governance and regulatory compliance. • Apply enterprise data management (EDM) standards and best practices throughout the data lifecycle. • Support data governance initiatives, including documentation, validation, and quality assurance activities. • Collaborate with cross-functional teams, including data analysts, software developers, architects, and business stakeholders, to understand data requirements and deliver effective solutions. • Support analytical environments focused on fraud detection, anomaly detection, financial oversight, and other data-driven initiatives. • Troubleshoot and resolve data pipeline, integration, and performance issues while continuously improving existing processes.

• Own the building, maintenance, and optimization of pipelines to ingest data from both operational databases and third-party tools into a data lake/warehouse. • Architect highly efficient ingestion patterns that handle evolving data schemas and high-volume, multi-source data streams seamlessly. • Optimize pipeline performance to ensure maximum uptime, high throughput, and cost-effective compute usage. • Use dbt to transform raw data within the data warehouse into structured, production-ready schemas. • Write templated SQL and Jinja code to enforce macro-driven, modular, and DRY (Don't Repeat Yourself) development practices. • Perform rigorous data quality checks by implementing native dbt tests. • Set up monitoring and alerting frameworks around both ingestion routines and dbt builds. • Track pipeline health metrics to measure and report on overall data freshness and platform reliability. • Build data applications that interact with the data warehouse to empower decentralized self-service analytics. • Build internal tooling and libraries to facilitate analytics and ML work.

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.