Data Engineer

Who is Recruiting from Scratch: Recruiting from Scratch is a premier talent firm that focuses on placing the best product managers, software, and hardware talent at innovative companies. Our team is 100% remote and we work with teams across the United States to help them hire. Data Engineer Location - New York, NY (On-site) - On-site role requiring five days per week in-office in New York City. Compensation - $200,000 - $250,000 Base + Competitive Equity Visa - Open to Visa Transfers and Visa Sponsorships Company Stage - Growth Stage - Series A / Early Growth Industry - Artificial Intelligence, Marketing Technology, Data Infrastructure, Consumer Data, Agentic AI, Enterprise SaaS, AI Automation About the Company Our client is building an AI-powered platform for marketing leaders that combines proprietary consumer data infrastructure with intelligent AI agents to automate data management, analytics, campaign generation, measurement, and reporting. At the foundation of the platform is a proprietary consumer graph covering hundreds of millions of U.S. consumers across thousands of attributes and historical data points. The company is building advanced agentic systems that can unify and standardize first-party brand data, train targeting models, generate insights, and automate operational workflows that traditionally require significant manual data and analytics work. The company is operating with a small, high-velocity technical team and works with leading consumer brands across multiple industries. As a Data Engineer, you'll own critical components of the data platform, including ingestion, transformation, data modeling, orchestration, storage, standardization, and the infrastructure required to support AI and agentic systems. This is an opportunity to work on massive-scale consumer data, build infrastructure that directly impacts enterprise customers, partner closely with Data Scientists, and help enable the next generation of AI-powered data products. What You'll Do Own ingestion, data modeling, transformation, and pipeline development across a massive consumer data platform Build and improve data pipelines supporting hundreds of millions of individuals and thousands of consumer attributes Design scalable systems for ingesting and processing first-party customer data Build and scale integrations with sales, marketing, CRM, advertising, and other systems of record Develop resilient data infrastructure supporting a growing multi-terabyte data footprint Design and maintain data models that power analytics, AI systems, and customer-facing products Build transformation workflows that standardize and normalize heterogeneous customer datasets Work with Snowflake and cloud-based lakehouse infrastructure to support large-scale data workloads Build and operate data orchestration pipelines using tools such as Dagster and dbt Design reliable data workflows that maintain high standards of data quality and consistency Partner closely with Data Scientists to productionize complex data and machine learning pipelines Scale data systems while maintaining performance, reliability, and data integrity Identify bottlenecks in existing pipelines and improve system efficiency Build infrastructure that enables AI and agentic access to structured and unstructured data Develop natural language retrieval APIs and structured data orchestration layers Enable AI agents to interact reliably with enterprise data systems Build data infrastructure that supports AI-powered analytics and decision-making Work across data engineering, analytics engineering, infrastructure, and AI platform systems Help build data products that directly support high-value enterprise customer contracts Translate complex business and data requirements into scalable technical solutions Operate independently and make technical decisions in a highly ambiguous environment Work closely with engineering, data science, and business stakeholders Improve the reliability, scalability, observability, and performance of production data systems Help establish data engineering standards, best practices, and technical processes Continuously evolve the platform as customer data requirements and AI capabilities expand Ideal Candidate Background Experience Requirements 1+ years of professional experience building and scaling data infrastructure Strong data engineering or analytics engineering background Experience building production data pipelines Experience with data ingestion, transformation, and modeling Experience working with cloud-based data warehouses or lakehouse systems Experience working with large or rapidly growing datasets Experience operating data infrastructure in production environments Experience building reliable and resilient data workflows Experience working closely with Data Scientists, Software Engineers, or analytics teams Experience working in fast-moving startup or high-growth environments preferred Strong ownership mentality with demonstrated execution ability Comfortable taking broad responsibility for data systems and infrastructure Ability to operate independently without heavy structure or hand-holding Strong analytical and problem-solving skills Comfortable working across data infrastructure and product requirements Strong interest in AI, agentic systems, and modern data platforms Ability to reason about data quality, scalability, reliability, and performance Comfortable working in a highly technical and high-velocity environment Technical Requirements Strong data engineering fundamentals Strong experience building production data pipelines Experience with Snowflake or comparable cloud data warehouses Experience with AWS or comparable cloud infrastructure Experience with Dagster, Airflow, Prefect, or comparable orchestration frameworks Strong dbt experience or comparable transformation tooling Experience with data modeling and analytics engineering Experience building large-scale ingestion systems Experience working with multi-terabyte datasets Experience with data lakes or lakehouse architectures Experience with Apache Iceberg or comparable table formats preferred Experience designing scalable data transformations Strong SQL experience Strong understanding of data quality and validation systems Experience building integrations with external systems and APIs Experience working with structured and semi-structured data Experience optimizing data pipelines for performance and cost Experience with distributed data processing systems preferred Experience enabling AI or agentic systems through structured data access preferred Experience building APIs or data access layers preferred Strong understanding of data architecture and system design Strong debugging and production troubleshooting capabilities Ability to reason about scalability, reliability, latency, and data correctness Ability to work across data infrastructure, AI systems, analytics, and product requirements Education Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or related technical field preferred Equivalent practical engineering or data experience accepted Strong computer science, data systems, statistics, and software engineering fundamentals Soft Skills Exceptional technical ownership Strong analytical and problem-solving ability Deep technical curiosity Strong data-oriented mindset Strong systems thinking Strong communication skills Comfortable working directly with technical and business stakeholders Comfortable working closely with Data Scientists and engineers High execution velocity Strong bias toward shipping Strong ability to reason from first principles Comfortable making technical decisions independently Strong architectural judgment Strong attention to data quality and correctness Pragmatic approach to technical tradeoffs Low-ego collaborative mentality Strong product and business orientation Strong customer empathy Comfortable working in ambiguous environments Comfortable managing multiple priorities simultaneously Strong ownership of production systems Comfortable working in a fast-moving startup environment Comfortable working five days per week in New York City Strong interest in AI-native and agentic data systems Compensation & Benefits Base Salary: $200,000 - $250,000 Competitive equity package Opportunity to build foundational data infrastructure at massive scale Opportunity to work with hundreds of millions of consumer records Opportunity to build data systems supporting AI-native products Direct impact on high-value enterprise customer contracts Exposure to Snowflake, AWS, Dagster, dbt, Iceberg, and modern data infrastructure Opportunity to work closely with talented Data Scientists and technical leadership Opportunity to build AI and agentic data access layers High-ownership environment with significant technical responsibility Opportunity to work on complex data engineering problems at scale Visa transfer and sponsorship support Why Join This is an opportunity to join a high-velocity AI company building one of the most sophisticated consumer data platforms in the market. You'll work on data infrastructure supporting hundreds of millions of consumers while solving difficult problems across ingestion, data modeling, transformation, orchestration, data quality, and AI-enabled data access. You'll have direct ownership over systems that power both the company's AI platform and high-value enterprise customer products. If you enjoy building large-scale data infrastructure, solving complex data problems, working closely with AI and Data Science teams, and operating with high ownership in a fast-moving technical environment, this role offers exceptional technical scope and impact. Recruiting from Scratch