[Remote] Senior Data Engineer, AI & Product Integrations
Note: The job is a remote job and is open to candidates in USA. Userflow is seeking a Senior Data Engineer to bridge their data lake and product. This role involves owning the pipelines, APIs, and real-time integrations that transform raw data into actionable product features and business insights, while leveraging AI for enhanced decision-making.
Responsibilities
- Own data insights that inform AI product features, and build internal AI workflows that enable data-driven decision-making for GTM teams
- Create and own real-time and near-real-time integrations that push aggregated data from the lake into the product (via APIs, webhooks, feeds, or integrations)
- Query and analyze the data lake using existing MCP and tools to surface insights that inform product and business decisions
- Design and build data pipelines that ingest new data from the product back into the data lake (occasional but critical)
- Write agentic code using Claude Code / Cowork to automate analysis, decision-making, and data movement (e.g., quickly prototype data transformations and integrations with AI assistance)
- Use agentic code to build Streamlit dashboards, notebooks, and quick analysis tools to explore data and validate hypotheses
- Collaborate with product, engineering, and rest of data engineering teams to understand data needs and translate them into integrations
Skills
- 5 years of software engineering or data engineering experience
- Experience shipping production level code using AI backed pipelines
- Experience working with data lakes, data warehouses, or similar big data systems (e.g., Snowflake, BigQuery, DuckDB, etc.)
- Familiarity with SQL and querying large datasets
- Experience building or consuming APIs, webhooks, or event-driven integrations
- Some exposure to ETL pipelines or data engineering tools (Airflow, dbt, custom scripts, etc.)
- Familiarity with MCPs (Model Context Protocols) or LLM-driven tooling
- You're comfortable using AI tools (Claude Code, Cowork, etc.) to move faster and experiment with solutions
- You think in terms of how can I automate this with AI rather than how do I do this manually
- You care about data quality and understand the importance of reliable pipelines
- You're curious about what data can tell us and eager to dig into questions
- You're pragmatic: you'll ship a Streamlit prototype today over a perfect pipeline next month
- You communicate clearly with non-technical stakeholders (product, business) about what data can and can't do
- Experience with streaming or real-time data (Kafka, Pub/Sub, webhooks)
- Experience with Streamlit or similar rapid dashboard tools
- Exposure to SaaS product metrics and analytics
- Comfort with async work and distributed teams
Benefits
- Work that matters: you're directly enabling product decisions and customer value
- Autonomy: you own the data integration layer end-to-end
- Modern tools and practices: AI-driven development, agentic workflows, rapid iteration
- Competitive compensation and benefits
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