Snowflake / HoneyDew Data Engineer
About the Role
We're looking for a Snowflake and semantic-layer engineer to own the data layer that powers our enterprise BI migration platform. You'll engineer the Snowflake objects, author the HoneyDew semantic models, and ensure performance and parity for Power BI consumption at scale.
Key Responsibilities
- Perform Snowflake schema introspection and prepare schema metadata to feed automated semantic layer generation.
- Engineer and certify Snowflake objects (tables, views, secure views, materialized views, dynamic tables) that underpin HoneyDew domain definitions.
- Author and review YAML metric definitions for HoneyDew semantic models; version-control all artifacts in Git.
- Validate Change Data Capture (CDC) pipelines from upstream sources (Salesforce, ERP, marketing platforms) landing into Snowflake.
- Partner with client data engineering teams on integrating Data Vault structures with HoneyDew exposure patterns.
- Tune Snowflake performance for Power BI consumption — make data-driven decisions on Import vs. DirectQuery vs. Composite model strategies.
- Collaborate with dbt-based transformation workstreams; review and contribute to dbt models, tests, and documentation.
- Support integration with ingestion platforms such as C-Data Sync and Informatica IICS feeding Snowflake.
- Work with QA and reconciliation leads to support 5-dimension parity validation (row-level, aggregate, filter logic, schema, performance).
Required Skills & Experience
Snowflake
- 5-8 years of hands-on Snowflake experience in production environments
- SnowPro Core Certification mandatory
- Expert-level SQL — advanced window functions, recursive CTEs, query profiling, performance tuning
Semantic Layer
- Working knowledge of semantic layer platforms — HoneyDew strongly preferred
- Equivalent experience with dbt Semantic Layer, AtScale, Cube.dev, or Looker LookML also considered
- Strong YAML proficiency for declarative model and metric authoring
Data Modeling & Transformation
- Production dbt experience (dbt Core or dbt Cloud) — building, testing, and deploying models
- Data modeling fundamentals: dimensional modeling (star / snowflake)
- Proficiency with Git-based version control workflows (branching, pull requests, code review)
Communication
- Excellent communication skills; comfortable in client-facing collaboration with international teams
- Willingness to work in overlap windows with US-based stakeholders when required
Preferred / Plus
- +SnowPro Advanced (Architect or Data Engineer) certification
- +Data Vault 2.0 familiarity
- +Understanding of Power BI data connectivity patterns (Import / DirectQuery / Composite)
- +Familiarity with Salesforce data model and Salesforce-to-Snowflake CDC integration patterns
- +Expertise in BI Reporting
- +Production experience with HoneyDew semantic layer
Frequently asked questions
About CodeHive Labs
CodeHive Labs Private Limited is an India-based product company building agentic AI platforms for enterprise Business Intelligence migration. Our flagship AI Workspace automates migration of legacy BI reports — Tableau, SAP BusinessObjects, Cognos, MicroStrategy — to Microsoft Power BI using multi-agent AI. Built on Microsoft Azure. Serving Fortune 500 enterprises globally. Multiple provisional patents filed.
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