Role Description We are seeking Freelance Data Engineer to support the implementation, orchestration, and optimization of customer data and analytics solutions. This role sits at the intersection of Data Engineering and Analytics Implementation, requiring a strong understanding of data collection, customer data platforms, analytics tools, and data movement across systems. The ideal candidate will have hands-on experience with Adobe Experience Cloud products, strong technical skills, and the ability to work independently while collaborating with cross-functional teams to deliver reliable data solutions and actionable insights. - Implement, configure, and support Adobe Experience Cloud solutions, including Customer Journey Analytics (CJA), Adobe Launch, Adobe Journey Optimizer, and Adobe Analytics. - Design, maintain, and troubleshoot data collection frameworks and tracking implementations. - Support data orchestration, transformation, and movement across multiple systems and platforms. - Work with Customer Data Platforms (CDPs) to ensure accurate data ingestion, activation, and reporting. - Develop and maintain data pipelines and data structures that support analytics and customer experience initiatives. - Collaborate with engineering, analytics, and business teams to define tracking requirements and data strategies. - Validate data quality, troubleshoot implementation issues, and ensure reporting accuracy. - Document implementation processes, data flows, and technical requirements. - Manage multiple priorities while working independently in a fast-paced environment. Qualifications - Hands-on experience with Adobe Experience Cloud tools, specifically: - Adobe Customer Journey Analytics (CJA) - Adobe Launch - Adobe Journey Optimizer - Adobe Analytics - Strong JavaScript skills. - Experience working with databases and data management solutions. - Experience with Customer Data Platforms (CDPs). - Strong understanding of data engineering concepts, including data structures, data modeling, and data pipelines. - Experience with data orchestration and data movement across platforms. - Experience implementing website data collection and tagging solutions. - Hybrid background spanning both engineering and analytics implementations. - Strong organizational, project management, and problem-solving skills. - Ability to work independently with minimal supervision. - Excellent communication skills and professional fluency in English. Requirements - This role is currently not available for hire or work in New Mexico and Hawaii, USA. Benefits - Freelance contract opportunity with the possibility of extension based on project needs and performance. - Contract Start Date: June 22, 2026 - Contract End Date: July 31, 2026 - Total Hours: 232 - Engagement Type: 1099 or W2 (depending on final worker classification) - Equipment: Candidates must use their own computer and equipment. Company Description Huge is a design and technology company. We create products and experiences that grow the world’s most ambitious brands. We do this by designing experiences for people, not users, and uncovering new sources of growth by leveraging our creative talent, our proprietary platform LIVE and unlocking the advantages brought to us by emerging technologies. Huge’s nearly 1,000 thinkers, tinkerers, makers and creators, have been problem-solving across North America, Europe, and Latin America for over 25 years. Huge is committed to creating an inclusive employee experience for all. Regardless of race, gender, religion, sexual orientation, age, disability, or if you’re parenting the next generation of innovators, we firmly believe that our work is at its best when everyone feels free to be their most authentic self. Huge is an equal opportunity employer (EOE). We strongly support diversity in the workforce. We are committed to an inclusive, barrier-free recruitment and selection process and work environment. Workers shall not be required to pay employers’ or agents’ recruitment fees or other related fees for their employment. The salary range for this position is as listed below. Exactly where a prospective employee will be paid within this range will depend on various factors. Wage Disclosure: $50 — $60 USD

Role Description As a Senior Staff Data Engineer at Afresh, you'll be one of our most senior individual contributors — setting technical direction for how we build, integrate, and scale the data systems that power Afresh's products. You'll own some of our most complex and ambiguous data problems end to end: - From raw data ingestion through transformation and delivery to downstream product and ML teams, across both new and existing customers. - Define the architecture, abstractions, and tooling that make every future integration faster and more reliable. - Influence direction across teams, mentor other engineers, and partner closely with Product, ML, Solutions Engineering, and customer-facing teams. What You'll Do - Architect and build core data systems and pipelines that power Afresh products, owning reliability and quality from raw data through to production. - Take on our most ambiguous, high-leverage data problems and drive them to a shipped solution — without waiting for a detailed spec. - Set technical direction: define the architecture, patterns, and abstractions that make customer integrations and product dataflows faster, cleaner, and more repeatable over time. - Drive data quality and pipeline reliability — invest in better alerting, self-healing patterns, and resilience to messy or incomplete real-world customer data. - Champion AI-forward engineering: evaluate and adopt AI tools and agentic workflows that accelerate development, automate repetitive work, and push the team to the bleeding edge of modern data engineering. - Raise the bar technically — review code and architecture decisions, pair with engineers on hard problems, and mentor across the team. - Collaborate deeply with Product, ML, Solutions Engineering, and customer-facing teams to scope work, unblock dependencies, and ensure what we build meets real customer needs. Qualifications - Extensive experience (typically 8+ years) building data engineering systems, with a track record of operating at a staff or principal level. - Deep technical expertise across Python, PySpark, SQL, dbt, Airflow, and modern data platforms (Databricks, Snowflake, or similar). - A history of shipping high-quality data integrations or ETL systems at scale, and a deep understanding of what makes data pipelines reliable. - Proven ability to own ambiguous, end-to-end problems and set technical direction in a fast-moving environment with no established playbook. - Genuine enthusiasm for AI-augmented engineering. - Comfort working with messy, real-world data from enterprise customers, and the pragmatism to ship solutions that work without over-engineering. - Strong collaboration and influence skills. Nice to Have - Experience in grocery, retail, or supply chain data domains. - Prior experience at a high-growth startup navigating rapid customer expansion. - A history of acting as a technical leader who sets direction across multiple teams or projects. Our Tech Stack - Python, PySpark, dbt - Databricks (Delta Lake, Unity Catalog) - Astronomer (Airflow) for orchestration - Claude, GitHub, Shortcut, Notion for development workflows Salary Range Salary Range in U.S.: $191,000- $287,000 Benefits - Comprehensive medical, dental, and vision coverage for you and your family, with the majority of premiums covered by Afresh. - Dedicated mental health support and counseling services. - Competitive base salary, meaningful equity (U.S. employees), and a 401(k) program with a generous company match. - Home office stipend and "Coworking Wallets" for flexible workspace access. - Annual professional development budget to master new skills and grow your career at Afresh. - Monthly stipends for "Betterment" (wellness/lifestyle) and telecommunications. - Flexible paid time off to recharge.

• Develop and maintain SQL code and SSIS packages. • Analyze data and solve new and existing business issues. • Reviewing query performance and optimizing code. • Provide production level support. • Fully document all processes that are being created.

• Design, implement, and continuously improve systems for data ingestion, processing, storage, and sharing • Build and optimize data architectures for performance, scalability, and reliability • Develop and maintain ETL/ELT pipelines using modern tools and frameworks • Ensure seamless integration and synchronization across systems • Uphold high standards of data quality, security, availability, and performance • Collaborate with analysts, software engineers, and business stakeholders to understand data needs and deliver solutions • Perform code reviews, troubleshoot software, and fix defects • Implement monitoring and alerting for data workflows • Gain expertise in a variety of banking processes and products