Data Engineer

At Qualitate, you’ll help build the data infrastructure behind AI moderation and customer-ready, structured insights. As the first dedicated Data Engineer, you’ll design and deliver reliable data pipelines, AI-powered enrichment workflows, and the data models that keep information consistent, searchable, and dependable. This role pairs high ownership with a fast-moving team focused on quality, impact, and a collaborative, enjoyable working environment.

What you’ll do

• Build and maintain data pipelines using ETL/ELT patterns to ingest unstructured data, quantitative metrics, and third-party datasets into core systems.
• Design and evolve data models across both relational and non-relational systems, shaping how downstream products use data.
• Create AI-powered data enrichment pipelines that use LLMs and other AI systems to extract structured information from unstructured sources, classify and enrich records, and integrate outputs into production workflows and evaluation systems.
• Own data quality end-to-end by implementing automated QA checks, monitoring, and alerting to catch anomalies before they reach clients.
• Partner cross-functionally with Research, Applied AI, and Engineering to define schemas, data contracts, and reporting needs as new features launch.
• Document as you build with clear data lineage, schema documentation, and runbooks to establish a strong data foundation.

What you bring

• Strong SQL skills, including writing complex, performant queries and reasoning about data at scale.
• Production-quality software engineering ability, with experience in either TypeScript or Python for automation, pipelines, integrations, and internal tooling.
• Experience building robust data integrations involving APIs, databases, files, authentication, pagination, rate limits, incremental extraction, retries, schema-change handling, and error management.
• Capability to research and integrate third-party datasets, including identifier work, entity-matching strategies, corporate hierarchies, subsidiaries, acquisitions, and cross-source reconciliation.
• Comfort across data types (structured, semi-structured, unstructured), with awareness of tradeoffs between relational databases, object storage, search/indexing systems, and analytical stores.
• Experience working with the current stack, including maintaining TypeScript pipelines on scheduled jobs and Postgres-native queues, using S3 for object storage, and AWS Bedrock for retrieval.
• Plus: experience with a modern warehouse and transformation stack (e.g., Snowflake/BigQuery, dbt, Airflow).
• Works well with ambiguity and enjoys building structure in early-stage data infrastructure.

Technologies you’ll work with

SQL, TypeScript, Python, S3, AWS Bedrock, Postgres, Snowflake, BigQuery, dbt, Airflow

Benefits

• Base salary: $170,000 to $200,000 per year (depending on experience)
• Bonus: eligible for a cash bonus tied to individual and company performance
• Equity: meaningful early-stage grant with upside tied to company growth
• Benefits: health coverage, flexible PTO, paid holidays
• Location: full-time, in-person in New York City

What sets you apart

• Prior data engineering experience at a technology startup, ideally in fintech
• Early involvement on an engineering team where you helped build the function from scratch
• Exposure to LLM-driven data pipelines such as labeling, moderation, or quality scoring
• Experience in market research, expert networks, or financial services, with comfort working to high data integrity standards

What working at Qualitate is like

• Excellence: a high bar for quality and impact
• High velocity: fast-paced growth, decision making, and time to impact
• High agency: ownership over how you work
• Shared ambition: disrupting the multi-billion dollar market research industry with AI as a small early team
• Joy: hard work paired with a collaborative, enjoyable environment