• Manage a team of Data Engineers and Data Analytics Engineers owning our data infrastructure, including our medallion layers, data pipelines, and collaborating closely with MLEs on LLM Operations and agentic products. • Navigate ambiguity, driving innovation through rapid prototyping and iterative development in cross-functional teams • Partner with function leads and senior leadership to align growth paths, performance expectations, and strategic goals with technical excellence standards. • Translate the Data Engineering vision into clear objectives, priorities, and milestones, ensuring effective project scoping, resourcing, and delivery. • Define and refine agile workflows tailored to data engineering, managing key rituals such as design sessions, sprint planning, and retrospectives. • Serve as the primary delivery interface across Product, Engineering, and Customer Success, ensuring alignment, transparent communication, and continuous improvement of team operations. • Drive hiring excellence by attracting, developing, and scaling a high-performing team aligned with business needs.

• Design and implement dimensional and normalized data models optimized for analytical workloads in lakehouse environments. • Build and manage modern data lakehouse solutions using AWS services including Amazon S3, AWS Glue, Amazon Redshift Spectrum, and Lake Formation for governance, cataloging, and fine-grained access control. • Develop, monitor, and optimize batch and near-real-time data pipelines using AWS Glue, AWS Lambda, Amazon Kinesis, and Step Functions. • Ingest structured, semi-structured, and unstructured data from APIs, databases, streaming sources, and third-party systems into the lakehouse. • Define and manage data infrastructure using AWS CloudFormation, CDK, with CI/CD pipelines. • Support model training and analytics initiatives by preparing datasets, performing analysis with strong attention to detail, and creating visualizations using AWS Quick Suite. • Perform other duties as assigned.

Afresh is the leading AI company in fresh food—partnering with grocers like Albertsons, Wakefern, Meijer, and Stater Bros to order billions of dollars of fresh food in over 12,000 grocery departments nationwide. Following record-breaking 70% growth in 2025, we’ve expanded our platform to cover all fresh departments, launched our full store suite, and debuted DC Fresh Buying. We’re on a mission to eliminate food waste and make fresh food accessible to all. In 2025 alone our software helped save 200M lbs of food waste. If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines the future of fresh, there is no better time to join us. About the Role As a Senior Data Engineer, you’ll play a key role in scaling and improving how we integrate and process customer data. You will design and implement ETLs that reliably process large volumes of customer-provided data and build tools/improve the platform to make customer integrations faster, more accurate, and more scalable. You’ll also contribute to the development of new features that support our expanding product lines. Your work will have a direct and visible impact on our ability to onboard customers more easily and quickly and power our machine learning grocery solution. What You’ll Do Build tools and frameworks that streamline customer integrations, enabling faster onboarding and better handling of customer data. Create robust ETLs in PySpark and DBT to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use. Investigate and implement new technologies into the data platform, focusing on practical solutions that address current pain points and anticipate future needs. Collaborate with product, engineering, and go-to-market teams to design and deliver data solutions for new products and features. Identify and implement optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations. Solve real-world data quality challenges by working directly with messy, incomplete, or inconsistent customer data to extract the signal we need. Support team members by mentoring engineers, leading technical discussions, and providing clear, actionable feedback. What Makes You a Great Fit We encourage all highly-qualified candidates to apply, even if they don’t meet every listed qualification. Salary Range in U.S.: $156,000 - $211,000 Salary Range in Canada (CAD): $137,000 - $185,000 About Afresh Founded in 2017, Afresh is working on the #1 solution to curb climate change: reducing food waste. By combining human insight and transformative technology, we're helping grocers provide fresher food to customers at more affordable prices. Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals including ICML, and we've raised over $148 million in funding from investors including former co-CEO of Whole Foods Market Walter Robb and Eric Schmidt's Innovation Endeavors. Fresh is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility. Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law. Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI .

Company Description DevIQ specializes in building modern cloud and data solutions – and we believe in the power of software and technology to improve lives. Join us to partner with passionate mid-market companies focused on reducing energy costs, curing disease, improving education, building smart cities, and more. From true innovation and synergetic cloud & technology partnerships to competitive full-time benefits and a strong team culture, DevIQ is a great place to work. At DevIQ, you’ll: Build your career with a supportive, inclusive team that appreciates people, creates value, embraces growth, and “owns the problem” as a team. Enjoy opportunities to learn, exposure to new industries, and building end-to-end solutions through meaningful work on active client projects. Work remotely and/or from our modern studio in downtown Denver. Bring your unique perspective and experience to multi-disciplinary teams. Collaborate on and contribute to transformative digital experiences that touch millions of lives, watching your work make an impact. Please note that you must be a U.S. citizen or eligible to work in the U.S. to be considered for this role, and third-party candidates will not be accepted. Job Description We are seeking a Data Engineer to join our growing team. In this role, you’ll build robust and scalable data pipelines that support high-quality analytics and machine learning solutions for our clients. You’ll play a critical role in designing workflows that ingest, transform, clean, normalize, and augment data from various sources. You should be comfortable working in cloud-based environments and have experience with structured and unstructured data. A strong command of SQL and Python is essential, along with practical experience using Pandas, Apache Spark, or similar data transformation frameworks. Key Responsibilities: Design and build reliable, scalable data pipelines for ingestion, transformation, normalization, and augmentation Work with structured, semi-structured, and unstructured data across diverse environments Develop approaches to source data from diverse platforms (flat files, databases, APIs, streams, etc.) Develop data transformation workflows using tools such as Pandas and Apache Spark Collaborate with cross-functional teams to gather data requirements and translate them into actionable data models Qualifications Required: 3+ years of hands-on experience with SQL and Python in data engineering or analytics roles Experience with data transformation tools/frameworks such as dbt, Pandas and Apache Spark Familiarity with cloud data platforms (e.g., Azure, AWS, Databricks) Solid understanding of ETL/ELT processes and pipeline orchestration Experience using version control systems like Git Strong communication and problem-solving skills Proactive in seeking opportunities to learn and grow skillset Preferred: Experience with Databricks, including use of Delta Lake, Spark notebooks, and Unity Catalog in production environments Experience with modern Data and ML workflow tools (e.g., Airflow, MLflow) Familiarity with data visualization libraries or tools (e.g., matplotlib, Power BI, Tableau) Understanding of best practices in data modeling, data quality, and pipeline monitoring Prior experience in a consulting or client-facing role Additional Information Est. Salary Range (Colorado Only): $120,000-$140,000* *Disclaimer: In accordance with Colorado’s Equal Pay for Equal Work Act, effective January 1, 2021, a good faith hourly or base salary range must be posted for all positions where the work may be performed in the state of Colorado. Therefore, this good faith salary range will only apply where this described position will be performed in the state, and should not be considered the compensation range in other locations or for other positions. DevIQ Benefits Include: Competitive financial compensation and utilization bonus plans Medical, Dental, Vision Insurance 401k, With 4% Matching Paid Time Off Health Savings Account (HSA)/Flexible Spending Account (FSA) Short-Term/Long-Term Disability Insurance Business funded Life Insurance Plan Dynamic yet relaxed work atmosphere Wide Variety of Growth Opportunities