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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer 2 - **Company:** The Farmers Dog - **Location:** New York, NY, United States - **Experience:** Experienced - **Salary:** $130,000.0 - $145,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Business Analytics Applications, Data Analysis, Software Code Optimization, Databases, Data Cleansing, Information Engineering, Data Governance, Data Infrastructure, Data Integrity, Extract Transform Load (ETL), Data Transformation, Data Warehousing, File Systems, Python (Programming Language), Machine Learning, Operational Databases, Standard Sql, Software Engineering, Data Streaming, Unstructured Data, Data Processing, Kubernetes, Production Code, Machine Learning Operations, Restful APIs, Data Pipelines - **Published:** October 13, 2026 - **Apply:** https://startup.jobs/data-engineer-2-the-farmers-dog-10461649 ## About the Role * You have 2-4 years of experience in data engineering, software engineering, or related technical field * You're proficient in Python with experience writing production code, and have solid SQL skills for data transformation and analysis * You have experience or strong interest in AI/ML workflows and tooling, including data preparation for machine learning models --> bring this one up * You have practical experience with REST APIs and data integration patterns for ingesting data from multiple sources * You're familiar with data processing tools like DBT, Airflow, or similar orchestration frameworks * You understand ETL/ELT concepts and have built data pipelines independently with minimal guidance * You're comfortable collaborating with cross-functional teams to understand data requirements and deliver solutions and you have experience communicating technical concepts effectively to both technical and non-technical stakeholders. * You're detail-oriented with strong problem-solving skills and can manage multiple priorities effectively * You are eager to learn new technologies, expand your skill set in a fast-paced environment, and take initiative to optimize systems. * You love dogs. Office Guidelines We are an in-office culture, made of in-office people who thrive on the collaboration and magnetism of working in a shared space. We are seeking individuals who excel in this type of environment, where being present fosters deeper connections and engagement. We ask all team members to be in office 4 - 5 days a week to build a collaborative and invested environment to foster our unique in-person culture we are proud to have. This office policy is subject to change at company discretion. ## Description The Farmer's Dog is seeking a Data Engineer 2 to join our growing group! You will maximize your technical expertise and data analysis skills to develop, implement, and maintain data analytics solutions within the organization. This role will collaborate with cross-functional groups - including data scientists, data engineers, and business partners to gather requirements, design data models, build data pipelines, and deliver practical insights. You will be critical to ensure data integrity, optimize data workflows, and enabling partners to make effective decision-making rooted in data. If you have a genuine love for data, technology, problem-solving and want to improve how The Farmer's Dog makes strategic decisions at the company level, then this is the role for you! One Team: We don't think of ourselves as "Acquisition Marketers", "Engineers", "Data Analysts", or "Product Managers". Beyond denoting skill sets and areas of expertise, we don't think departments matter. We'd rather align ourselves to the goals we're working to achieve and make sure we have necessary subject matter expertise to drive meaningful impact. We strive to orient ourselves around customer problems TOGETHER - getting the right people, with the right context, in the right rooms/Zooms to solve problems holistically. We are skeptical about everything and precious about nothing: Ideas can and should come from anywhere, and we aren't tied to our own. We proactively source input. We talk to our customers and leads regularly and are quick to change course if we know there's a better or more impactful way to solve problems. We consider the customer journey in all of our decisions: We know that no interaction exists in a silo and therefore understand how important every single one is. We ensure our strategy sets prospective and new customers up for success and drives long-term retention. We answer questions and address problems early and proactively. We understand the value of different channels, initiatives, and messages and know how to articulate impact and advocate for prioritization holistically. We Execute For Impact: We don't subscribe to "best practices" or "industry KPIs". We're uninterested in how we compare to "benchmarks"; instead we orient ourselves around being the best we can possibly be. Similarly, we don't subscribe to rigid or classical expectations of roles - i.e. acquisition is hyper-focused on improving customer retention and experience., * Build and maintain data pipelines for structured and unstructured data supporting reporting, analytics and AI/ML use cases. * Write production-level code that processes and validates millions of events per day. * Develop AI tooling and automation to enhance data engineering capabilities and workflows. * Ingest data from APIs, databases, file systems, and streaming platforms into our data infrastructure, and build and maintain pipelines for structured and unstructured data that support reporting, analytics, and AI/ML use cases. * Establish and maintain robust data governance frameworks across our data warehouse to ensure data integrity, reliability, and security across the organization * Implement monitoring, data quality checks, and alerting to ensure pipeline reliability and implement automated checks. * Support production data systems and help resolve data-related incidents. * Document technical implementations, follow engineering best practices, and foster a collaborative team environment that promotes knowledge sharing, standard methodologies, continuous improvement, and continuous learning.