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

Company Overview