Role Description As a Remote Data Processing Specialist, you'll ensure the accuracy, consistency, and security of our case and client-related data, even while working remotely. Your role is essential to enabling our litigation teams—handling automotive defense, consumer protection, and business disputes—to access reliable, up-to-date information without interruption. Responsibilities & Duties - Digital Data Management & Integrity - Enter, update, and maintain case-related data in the firm's systems with precision. - Conduct validation checks to catch errors and maintain high-quality structured data. - Generate routine reports, summaries, and status updates from processed data. - Document Processing & Quality Control - Estimate metadata for digital documents, ensuring accurate indexing and retrieval. - Compare source documents against system entries, identify inconsistencies, and make corrections. - Remote Workflow & Collaboration - Collaborate virtually with attorneys, paralegals, and other staff to ensure data consistency and resolve queries. - Maintain confidentiality when handling sensitive legal information in a remote environment. - Process Documentation & Reporting - Draft and follow standard operating procedures for data handling and data correction protocols. - Escalate critical data issues when appropriate and document resolution steps. Qualifications - Minimum: High school diploma or equivalent; Bachelor's degree preferred. - 2+ years in data processing, legal support, or data specialist roles; familiarity with litigation workflows is a plus. - Skilled in Microsoft Excel and Office tools; experience with data validation, reporting software, or statistical packages (e.g., SPSS) is a plus. - Strong attention to detail, self-motivated, effective remote communication, and high-level of discretion. - Reliable internet connection and a functional home office setup. Why This Role Is Critical to Park Lawless & Tremonti LLP Given the firm’s focus on intricate litigation—requiring airtight documentation and accurate data tracking—the Remote Data Processing Specialist ensures that attorneys have immediate access to critical information, boosting case readiness and operational efficiency even across distances.

Data Engineer - AWS Bedrock & Microsoft Fabric Location: Canada / United States (Remote) Type: Contract Overview A leading energy-sector enterprise is seeking 1-2 experienced Data Engineers / Data Scientists to join a growing data and AI team. This role will support the advancement of AI-enabled use cases and a strategic migration from AWS Redshift to Microsoft Fabric as the organization's go-forward enterprise data lake. This is a hands-on development role working closely alongside Business Analysts and data stakeholders, ideal for candidates with strong data engineering fundamentals and practical experience across AWS Bedrock and Microsoft Fabric. Team & Working Model - You will work as 1 of 1-2 Data Engineers / Data Scientists supporting a team of 3 Business Analysts - Fully remote is acceptable due to the development-focused nature of the role - Candidates must be aligned to MDT working hours Key Responsibilities - Design, build, and optimize scalable data pipelines and data services supporting analytics and AI workloads - Implement and support data engineering components leveraging AWS Bedrock - Contribute to the development and operationalization of AWS Bedrock AgentCore (limited exposure is acceptable) - Support the migration of the enterprise data lake from AWS Redshift to Microsoft Fabric - Develop and maintain data models, ingestion pipelines, and transformations within Microsoft Fabric - Ensure data quality, performance, security, and governance across cloud data platforms - Collaborate closely with Business Analysts, data scientists, and architects to translate business requirements into technical solutions Required Qualifications - Strong Data Engineering background with proven hands-on experience in development-focused roles - Experience working with AWS Bedrock (core requirement) - Exposure to AWS Bedrock AgentCore (up to ~6 months of experience is acceptable) - Hands-on experience with Microsoft Fabric, including data engineering or lakehouse workloads - Experience supporting or executing data platform migrations (e.g., Redshift to Fabric or similar) - Strong SQL skills and experience working with large-scale datasets - Experience operating in modern, cloud-based data architectures Nice to Have - Experience supporting AI/ML or GenAI-driven platforms - Familiarity with Databricks or adjacent analytics tools - Background in energy, utilities, or other asset-intensive enterprises - Experience working closely with business-facing teams (e.g., BAs, product owners) Everforth Apex is a world-class IT services company that serves thousands of clients across the globe. When you join Everforth Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRated's Best of Staffing in Talent Satisfaction in the United States and Great Place to Work in the United Kingdom and Mexico. Everforth Apex uses a virtual recruiter as part of the application process. Click here for more details. Everforth Apex Benefits Overview: In terms of professional development, Everforth Apex hosts an on-demand training program, provides access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and certification discounts and other perks to associations that include CompTIA and IIBA. Employee Type: Contract Remote: Yes Location: Calgary, AB, CA Job Type: Date Posted: May 6, 2026 Pay Range: $90 - $115 per hour Similar Jobs - Data Engineer - Data Engineer - Data Engineer - Data Engineer - Data Engineer

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 .