Forward Deployed Data Engineer (Integration)
Forward Deployed Data Engineer building hybrid data pipelines and semantic layers for Hilbert's AI Growth Engine. Implements warehouse-native or managed ClickHouse integrations, partners with AI agents for accelerated onboarding, and ensures reasoning consistency across customer environments.
About the job
Responsibilities
- Own the technical lifecycle of new customers, choosing and implementing the best deployment path (Managed Clickhouse vs. Warehouse-Native).
- Use Hilbert internal Discovery Agent to create reports and suggest mappings, moving from raw data to a working v1 pipeline in record time.
- Architect the semantic definitions for custom enterprise data, ensuring our agentic conversation engine has the "Ground Truth" for every query.
- Transform diverse source data into Hilbert unified growth models to power our generic ML systems.
- Act as the lead technical resource for high-stakes enterprise implementations, ensuring our stack is "packaged" and performant in their specific infra.
- Partner with the Data Discovery Agent to analyze customer data, suggest mapping alternatives, and generate the first version of pipelines automatically.
- Define metadata and business logic so our agentic flows can understand custom columns without hallucination.
- Ensure "Reasoning Consistency" so AI produces the same high-quality insights regardless of where the data resides.
Requirements
- Equally comfortable optimizing a Clickhouse query as writing native Snowpark (Snowflake) or BigQuery SQL.
- Comfortable implementing data orchestration scripts using Python.
- Understand that an AI needs context beyond just a table; discipline to define the "meaning" behind the data.
- Able to earn technical trust with a customer's Data Architect quickly, extracting the logic of custom tables and mapping them to Hilbert reasoning engine.
- Excited to use and improve AI agents that handle data discovery and pipeline scaffolding.
Nice-to-Haves
- Deep experience with dbt for warehouse-native modeling.
- Worked with more than one state-of-the-art data warehouse solution and knowing the optimization strategies.
- Experience with Semantic Layer frameworks (Cube, MetricQL, etc.).
- Background in E-commerce/Retail (understanding Revenue Metrics, Order lifecycle, LTV, CAC, and Attribution etc.).
- Having built an agentic workflow before.
Skills
ClickHouse, Snowflake, BigQuery, Python, SQL, Snowpark, Dagster, Airbyte, dbt, Semantic Layer, Cube, Metricql
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