Role Description Do you love turning complex marketing data into business-driving insights? Are you passionate about building scalable data pipelines that influence real revenue decisions? We are looking for a Data Engineer to join our growing data team and work at the intersection of data engineering, growth marketing, and decision intelligence. - Design and own scalable, reliable data pipelines using Python, SQL, and modern cloud tools - Lead ingestion and modeling of Meta Ads (Facebook) and marketing platform data - Build high-quality datasets that power campaign performance, attribution, and lead funnel analysis - Partner closely with marketing, growth, and product teams to translate business needs into impactful data solutions - Drive data quality, governance, and observability, ensuring data is trusted and actionable - Influence both technical architecture and business outcomes Qualifications - Strong hands-on expertise in Python and advanced SQL - Experience building ETL/ELT pipelines, working with APIs, and orchestration tools like Airflow - Solid understanding of Meta Ads ecosystem, attribution models, and lead-generation metrics - A mindset focused on ownership, impact, and scalable engineering practices Benefits - Work on high-impact problems in performance marketing and attribution - Own meaningful end-to-end data products, not just pipelines - Collaborate with smart, driven teams that value engineering excellence and accountability - Enjoy great perks – including a day off every 3rd Friday, wellness benefits, and more

Title: Remote Data Engineer I Location:Spartanburg, South Carolina, United States Beaumont Office Reporting and Analytics Days Job ID:P-105850 EX134 widget:Full Time 8 am to 5:30 pm Job Description: Job Requirements Build the Foundation for Data Driven Healthcare and Join Us as Our Next Remote Data Engineer I! Location: 100% Remote | Applicants must reside in one of the following states: AL, AZ, CT, DE, FL, GA, IN, KS, KY, LA, MD, MI, NC, PA, RI, SC, VA, WV, or WI. Why Choose Spartanburg Regional Healthcare System Spartanburg Regional Healthcare System is a forward thinking, community focused healthcare organization that has served the Upstate for more than 100 years. SRHS is committed to leveraging data, analytics, and emerging technologies to improve patient outcomes, support clinical decision making, and advance innovation across the enterprise. Team members at SRHS work in a collaborative environment that values learning, growth, and continuous improvement. Our data and analytics teams play a critical role in delivering trusted data that supports both business intelligence and advanced AI driven solutions. Step Into a Role That Builds Trusted Data at Scale Remote Data Engineer I The Remote Data Engineer I supports the implementation and maintenance of data pipelines and curated datasets that ensure data quality, consistency, and readiness for analytics and AI use cases. This role focuses on foundational data engineering activities, assisting with preparation, validation, and documentation of data so it is accurate, secure, and accessible for self-service reporting and advanced analytics. Working under the guidance of senior data engineers, this role develops skills in data curation, governance, and pipeline development while contributing to the delivery of reliable, optimized datasets that support both operational reporting and enterprise analytics initiatives. This is a fully remote position. What You Bring to the Table Educational Foundation - Bachelor’s or Master’s degree in Computer Science, Mathematics, or Information Systems Professional Experience - Minimum of 5 years of Business Intelligence or comparable data engineering experience (healthcare experience preferred) - Strong communication and analytical skills - Proficiency with Microsoft BI tools, T SQL, ETL processes, data modeling, and data visualization - Strong understanding of SQL and relational database concepts - Familiarity with Epic applications and Epic database structures Licenses and Certifications - Relevant Epic Data Model or Microsoft development certifications preferred - Certifications may include but are not limited to: - Epic Radar, Reporting Workbench Administration, Clarity Data, Caboodle, Slicer Dicer - Epic Revenue Cycle, Shared Clinical, Grand Central, and related specialties - AI development including machine learning and analytics platforms - Microsoft Fabric development including Data Warehouse, Lakehouse, and ETL tools - Microsoft SQL certifications What You Will Learn and Deliver - Assists with build and refresh activities using approved data architecture designs - Supports data ingestion and ETL processes including basic troubleshooting and data quality validation - Collaborates with engineers and developers to learn enterprise data standards and development patterns - Ensures compliance with data governance, security, performance, and privacy standards - Executes assigned project requests exceeding 40 hours under supervision - Contributes to continuous improvement of data reliability and usability - Performs additional duties as assigned Technologies and Work Areas You Will Support - Azure Databricks - Epic Caboodle development internal and external - Cogito Extract Scheduler - Cogito Reporting Workbench SQL - Cogito SQL Metrics - Copilot Studio agent development and management - Data agent development and management - Epic claims ingestion workflows - Microsoft Fabric Data Warehouse, Lakehouse, and ETL development - Power Platform applications - Power BI semantic model development and management - Slicer Dicer data model development and management - Other assigned or extended project requests Take the Next Step If you are ready to grow your data engineering skills, support meaningful analytics initiatives, and contribute to trusted data solutions that power healthcare innovation, we encourage you to apply today. Join Spartanburg Regional Healthcare System and help build the data foundation that supports smarter decisions and better patient care.

Role Description Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth. - Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business. - Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units. - Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth. - Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows. - Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity. - Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support. - Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture. Qualifications - 5+ years of experience in data engineering within fast-paced, cloud-native environments. - Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto). - Experience building and managing scalable ETL pipelines and data lake infrastructure. - Familiarity with distributed systems, Spark, and data quality best practices. - Strong cross-functional collaboration skills to support BI, analytics, and engineering teams. Requirements - 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations. Competencies - Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools. - Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions. - Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently. - Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows. - Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations. - Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering. Company Description Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. As The Discovery and Conversion Company, our mission is to connect consumers with the world’s leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, we’ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.

Role Description Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth. - Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business. - Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units. - Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth. - Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows. - Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity. - Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support. - Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture. Qualifications - 5+ years of experience in data engineering within fast-paced, cloud-native environments. - Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto). - Experience building and managing scalable ETL pipelines and data lake infrastructure. - Familiarity with distributed systems, Spark, and data quality best practices. - Strong cross-functional collaboration skills to support BI, analytics, and engineering teams. Requirements - 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations. Competencies - Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools. - Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions. - Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently. - Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows. - Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations. - Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering. Benefits Want to accelerate your career? Apply now! Since day one, we've been committed to having a diverse, inclusive team and culture. We are proud to be an Equal Employment Opportunity company. We value diversity, equity, and inclusion. We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.