Title: Staff Data Engineer Location DC Employment Type Full time Location Type Hybrid Department Engineering Compensation $215K – $250K Job Description: Meet Upside: We created Upside to transform brick-and-mortar commerce. Our technology uses the sophistication of online retail—profit measurement, attribution, and incrementality—to provide users with more value on their everyday purchases and brick-and-mortar businesses with new, profitable customers. We’ve helped millions of users earn 2 to 3 times more cashback than any other product, and hundreds of thousands of brick-and-mortar businesses earn measurable profit. Billions of dollars in commerce run through the Upside platform every year, and that value goes directly back to our retailer partners, the consumers they serve, and important sustainability initiatives. About the role: We're looking for a Staff Data Engineer to serve as a technical leader on the Analytics Engineering team. In this role, you'll drive the design and implementation of foundational data products and analytics platform capabilities that power Upside’s most critical product and business use cases. You’ll lead cross-functional workstreams, shape patterns and architecture across teams, and elevate the overall quality and impact of data work at Upside. This role is ideal for someone who enjoys deep technical problem-solving, cares about quality and long-term maintainability, and is motivated by helping others work more effectively with data. Here are some ways we have seen analytics engineers drive impact at Upside: - Design and deliver highly complex, domain-critical data products used by analysts, data scientists, and product teams to unlock new product features, ML models, and strategic decisions. - Architect scalable, extensible patterns for modeling, orchestration, and data transformation—balancing flexibility, reusability, and cost-efficiency. - Own platform evolution projects such as migrating the data platform to Snowflake Semantic Views, extending Cortex, or improving orchestration tooling for analytics workflows. - Lead technical planning and delivery across cross-functional teams, breaking down complex data initiatives into scoped, sequenced workstreams implemented by you and others. - Drive platform adoption and best practices, mentoring other engineers, building internal documentation and tooling, and raising the overall bar for analytics engineering across the company. - Influence upstream and downstream teams, partnering with engineering, product, data science, and business stakeholders to align on requirements and deliver end-to-end solutions. - Represent Analytics Engineering in technical design forums and contribute to roadmap discussions that shape the future of data at Upside. Why You Should Apply This role is a good fit for you if: - You aren’t afraid to challenge the status quo when it makes the team and business better. You learn from those around you while utilizing data to advocate for informed change. - You thrive at the intersection of systems and storytelling, not only building robust solutions but also communicating their purpose, impact and rationale, so teams can experiment, iterate, and act confidently. - You care about building resilient systems that scale. You bring a mindset of continuous improvement, and know when to invest in observability, automation, or new infrastructure to reduce toil and improve outcomes for the team and end users. - You believe that pulling quality upstream starts with engineering. You champion best practices, encourage early testing and validation, and work closely with peers to build a culture of quality from the ground up. Ideal Qualifications - Have 6+ years of experience in data or analytics engineering, with a track record of owning complex, business-critical data systems end to end. - Have deep expertise in SQL and Python, particularly for transforming, testing, and orchestrating very large datasets. - Are fluent with platforms like AWS, Snowflake, dbt, and Dagster, and can design extensible patterns to be used across teams. - Experience with DevOps practices (e.g., CI/CD for data), data governance, or FinOps (cost-conscious design). - Can break down ambiguous, cross-functional data problems and lead the implementation from design to deployment, collaborating across technical and non-technical teams. - Proactively identify opportunities to improve the analytics platform and are comfortable designing and implementing impactful, reusable solutions. - Communicate clearly across audiences, from engineers and analysts to product managers and business leaders. - Understand how to balance business value, maintainability, and platform standards in your design decisions. - Are excited about the opportunity to mentor others, set standards, and leave systems better than you found them. Preferred Qualifications - Experience supporting machine learning workflows, such as building features or monitoring model inputs and outputs. - Familiarity with DevOps practices (e.g., CI/CD for data), data governance, or FinOps (cost-conscious design). - Experience working in a fast-growing startup environment or on platform-style teams that serve internal customers. Engineering Culture: We want our engineers to have the time and support to grow in their craft and contribute meaningfully to impactful technical decisions. Engineers are encouraged to focus deeply on their work, collaborate effectively with team members, and continuously develop their skills. Teams are thoughtfully staffed to create a dynamic and diverse environment that enhances learning and innovation. Location: This role offers location flexibility, however, if you’re based in the Washington, D.C., Austin, Chicago, or NYC metropolitan regions, in-office attendance is required on a hybrid basis. Compensation: The US base salary range for this full-time position is $215,000 - $250,000 + equity + benefits. The final starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. Your recruiter can share more about the specific salary range during the hiring process. #LI-Hybrid #LI-NE1 Benefits: - Medical, dental, and vision coverage starting on Day 1 - Equity (ISOs) - 401(k) program - Family planning programs + paid parental leave - Physical fitness and wellness memberships - Emotional and mental health support programs - Unlimited PTO + 10 paid federal holidays + our annual, week-long Winter Break - Flexible work environment - Lunch reimbursement for in-office employees - Employee Resource Groups - Learning and Development stipend - Transparent culture - Amazing mission! Diversity and Inclusion: Diversity drives innovation, and our differences make us stronger. We‘re passionate about building a workplace that represents a variety of backgrounds, skills, and perspectives, and we do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Everyone is welcome here! If there's anything we can do to support a disability or special need during your application or interview process, please email. This email is for accessibility accommodations only, it should not be used to submit job applications. Notice To Recruiters And Placement Agencies: This is an in-house search with a dedicated recruiter. Please do not submit resumes to any person or email address at Upside. Upside is not liable for, and will not pay, placement fees for candidates submitted by any party or agency other than its approved recruitment partners.

Role Description We are sharing a specialised part-time consulting opportunity for professionals experienced in image quality review, dataset validation, annotation QA, rubric-based evaluation, visual content auditing, and structured data quality workflows. This role supports current and upcoming remote consulting opportunities focused on structured image dataset review, quality assurance, annotation validation, instruction review, benchmark development, and high-quality project execution. Selected professionals will apply strong visual judgment and attention to detail to review image data, identify quality issues, document findings clearly, and support consistent evaluation standards across image-based workflows. Key Responsibilities - Image Dataset Review & Validation - Review image datasets against defined quality standards, task instructions, and evaluation rubrics. - Validate image labels, annotations, classifications, metadata, or other visual data outputs for accuracy and consistency. - Identify inconsistencies, labeling errors, edge cases, unclear examples, and recurring quality issues. - Apply structured QA criteria consistently across large volumes of image-based review tasks. - Rubric-Based QA & Written Feedback - Evaluate visual data outputs using detailed quality rubrics and documented review standards. - Provide clear written feedback explaining quality issues, patterns, and recommended corrections. - Support structured review of annotation guidelines, instruction specs, and quality criteria. - Document findings in a way that is actionable, consistent, and easy for project teams to interpret. - Benchmarking & Quality Support - Contribute to quality benchmark materials, example sets, golden samples, and review documentation. - Support evaluation workflows involving image data, visual content, annotation outputs, and vendor-style quality checks. - Help maintain strong quality standards across image review and data validation deliverables. - Work independently while maintaining accuracy, consistency, and careful attention to detail. Qualifications - 2+ years of experience in QA, editing, auditing, reviewing, annotation, data labeling, content moderation, visual review, or related quality-focused work. - Experience applying rubrics, checklists, guidelines, or structured evaluation criteria consistently. - Strong attention to detail and ability to identify subtle visual inconsistencies or quality issues. - Clear written communication skills and ability to document findings in a structured, actionable way. - Ability to work independently, manage time effectively, and follow detailed task instructions. - Comfort working with image datasets, annotation tasks, visual content, or data quality workflows. Educational Background - A degree or professional background in data annotation, quality assurance, digital media, visual communication, design, information science, communications, editing, or a related field is helpful. - Equivalent practical experience in QA review, image annotation, visual content review, auditing, editing, or structured evaluation work is also highly relevant. Nice to Have - Experience with AI data annotation, model evaluation, image QA, computer vision data review, or dataset validation. - Familiarity with image labeling guidelines, annotation platforms, golden sample review, or quality benchmark workflows. - Experience reviewing vendor-submitted data, structured content outputs, visual datasets, or annotation quality reports. - Strong ability to apply detailed quality standards consistently and objectively. - Comfort providing concise, high-quality written feedback on visual or data-related issues. Why This Opportunity - Apply image review and QA expertise to structured remote project work. - Contribute to high-quality image dataset validation, annotation review, and data quality workflows. - Work on flexible, project-based assignments aligned with your review and quality assurance background. - Use your visual judgment in a focused, detail-oriented work environment. - Remote structure with competitive hourly compensation. Contract Details - Independent contractor role. - Fully remote with flexible scheduling. - Part-time commitment depending on project availability. - Competitive rates between $55–$70 per hour depending on expertise. - Weekly payments via Stripe or Wise. - Projects may be extended, shortened, or adjusted depending on scope and performance. - Work will not involve access to confidential or proprietary information from any employer, client, or institution. About the Platform This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams. By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy .

Role Description The Oncology Data Specialist serves as a valuable resource for oncology data, working in collaboration with physicians, administration, researchers, the oncology team, and other hospital departments. The Oncology Data Specialist ensures timely, accurate, and complete oncology data for the purpose of monitoring oncology outcomes, assessing patterns of care, monitoring quality of care and clinical practices, quality management and improvements, and program development. The Oncology Data Specialist follows data collection, reporting, and quality standards for compliance to the state, federal and oncology accreditation and regulatory agencies while managing and analyzing clinical information for education, research, and outcomes measurement. - Performs abstraction of patient cancer data into the cancer registry database by reviewing and interpreting complex diagnostic and treatment data from the hospital and physician office records. - Abstracts are efficiently and accurately codified using standards and practices defined by the American College of Surgeons (ACoS), Surveillance Epidemiology and End Results (SEER), American Joint Committee on Cancer (AJCC), and North American Association for Central Cancer Registries (NAACCR). - Utilizes all available data to assign staging to each applicable site, coding as required by above standard setters. - Performs case ascertainment to maintain a complete cancer registry database. - Identifies patients from ICD-10 codes of reportable malignant and benign diseases by reviewing pathology/cytology reports, diagnostic imaging reports, and physician dictation on inpatient and outpatient visits. - Identifies patients from radiation and medical oncology patient visits and determining reportability based on class of case after review of records. - Conducts data analysis and reports based on abstracted cancer registry data. - Prepares upon request reports on cancer patient data for the medical staff, medical students, Residents, Fellows, and hospital administration for the purposes of research and program development. - Ensures all reports are complete, accurate, high quality, and timely. - Performs high level follow up activities on all living patients abstracted into the cancer registry database, verifying cause of death using death certificate clearance process, and monitoring patients for their lifetime following the cancer diagnosis to assess the effectiveness of treatment. - As required for oncology accreditation, 90% of all living patients must have annually updated contact. Qualifications - Associate degree (60 college credits) or completion of/enrollment in National Cancer Registrars Association-Accredited Certificate Program (required) - Human Anatomy and Human Physiology (6 total credit hours) (required) - Registered Health Information Administrator (RHIA) or Registered Health Information Technician (RHIT) (preferred) Requirements - One year in a hospital or physician practice setting or 160-hour Clinical Practicum preparation for Certified Tumor Registrar exam (required) - Two years in a hospital or state cancer registry (preferred) - All employees in role must be eligible for the Certified Tumor Registrar (CTR) by the National Cancer Registrars Association (required) - If not already obtained, all new hires must obtain Certified Tumor Registrar (CTR) within two years of hire (required) Benefits - Assist in registry operations including training and developing new staff, creating and updating policies and procedures, participation on committees and participation in education as required to obtain the ODS certification and meet compliance with accreditation standards. - Participate in oncology accreditation activities, which includes case abstraction and continued monitoring of patients listed in the quality tools provided by the accrediting body (i.e. the Commission on Cancer Rapid Cancer Reporting System). - Maintains compliance with all company policies, procedures and standards of conduct. - Complies with HIPAA privacy and security requirements to maintain confidentiality at all times. - Performs other duties as assigned.

Role Description The Oncology Data Specialist serves as a valuable resource for oncology data, working in collaboration with physicians, administration, researchers, the oncology team, and other hospital departments. The Oncology Data Specialist ensures timely, accurate, and complete oncology data for the purpose of monitoring oncology outcomes, assessing patterns of care, monitoring quality of care and clinical practices, quality management and improvements, and program development. The Oncology Data Specialist follows data collection, reporting, and quality standards for compliance with state, federal, and oncology accreditation and regulatory agencies while managing and analyzing clinical information for education, research, and outcomes measurement. - Performs abstraction of patient cancer data into the cancer registry database by reviewing and interpreting complex diagnostic and treatment data from the hospital and physician office records. - Abstracts are efficiently and accurately codified using standards and practices defined by the American College of Surgeons (ACoS), Surveillance Epidemiology and End Results (SEER), American Joint Committee on Cancer (AJCC), and North American Association for Central Cancer Registries (NAACCR). - Utilizes all available data to assign staging to each applicable site, coding as required by above standard setters. - Performs case ascertainment to maintain a complete cancer registry database. - Identifies patients from ICD-10 codes of reportable malignant and benign diseases by reviewing pathology/cytology reports, diagnostic imaging reports, and physician dictation on inpatient and outpatient visits. - Conducts data analysis and reports based on abstracted cancer registry data, including calculation, analysis, and interpretation of data related to cancer occurrence, treatment, management, and outcomes. - Prepares reports on cancer patient data for the medical staff, medical students, Residents, Fellows, and hospital administration for the purposes of research and program development. - Performs quality assurance and auditing of registry data to ensure accurate, consistent, and complete data. - Performs high-level follow-up activities on all living patients abstracted into the cancer registry database. - Verifies cause of death using death certificate clearance process and monitors patients for their lifetime following the cancer diagnosis. Qualifications - Human Anatomy and Human Physiology (6 total credit hours) or equivalent job experience (required) - Registered Health Information Administrator (RHIA) or Registered Health Information Technician (RHIT) (preferred) - One year in a hospital or state cancer registry (required) - Two years in a hospital or state cancer registry (preferred) - Oncology Data Specialist-Certified (ODS-C) by the National Cancer Registrars Association (required) Requirements - Medical Terminology - Familiarity with requirements related to protected health information (PHI) and/or HIPAA - Detail-oriented in gathering relevant data while attending to essential details - Strong initiative - Ability to work independently - Must be able to communicate effectively in both verbal and written formats - Must be comfortable speaking to groups, such as with committee meetings - Must have ability to interpret an extensive variety of instructions and deliver results - Must have ability to define problems, collect data, establish facts, and draw valid conclusions - Must have ability to critically think through complex situations and make determinations based on presented data - Typing at least 60 words per minute - Proficient in Microsoft Office products including Excel, Word, PowerPoint - Capacity to learn other relevant systems and hospital medical records - Knowledge of database management Benefits - Demonstrates a commitment to service, organization values, and professionalism through appropriate conduct and demeanor at all times. - Maintains confidentiality and protects sensitive data at all times. - Adheres to organizational and department-specific safety standards and guidelines. - Works collaboratively and supports efforts of team members. - Demonstrates exceptional customer service and interacts effectively with physicians, patients, residents, visitors, staff, and the broader health care community.