Snowflake Data Engineer

Compunnel, Inc.; Richardson (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

Compunnel, Inc. is looking for a skilled data engineer based in Richardson, Texas. The role involves designing and operating data pipelines, focusing on Snowflake engineering, and developing AI-powered agents to enhance the platform's data intelligence.

The ideal candidate will have 8-10 years of experience in data engineering, proficiency in Python, and a deep understanding of multisource integration techniques.

Qualifications

• 8-10 years of experience in data engineering.
• Hands-on experience with Snowflake and advanced SQL.
• Experience with backend service integration using Python.

Responsibilities

• Design schemas and manage Snowflake environments.
• Build and maintain data ingestion pipelines.
• Develop backend integrations using REST APIs.

Skills

Snowflake engineering

ETL/ELT development

AI agent development

Backend API connectivity

Python

Multisource integration

Tools

PostgreSQL

Go (Golang)

Azure Data Factory

AWS

Job description

Job Summary

Responsible for designing and operating data pipelines that connect heterogeneous source systems, normalizing data into consumption-ready models in Snowflake, and building AI-powered agents that surface intelligence across the platform.

Key Responsibilities

• Snowflake engineering: Design schemas, write performant SQL, manage roles, warehouse sizing, and implement change management practices.
• ETL/ELT development: Build and maintain pipelines that ingest from diverse sources (APIs, databases, event streams) and normalize data for BI and downstream consumers.
• AI agent development: Leverage Snowflake Cortex and AI agent frameworks to build intelligent data products and automate analytical workflows.
• Backend API connectivity: Develop backend integrations with internal and third‑party systems via REST APIs and backend services.

Required Qualifications

• 8-10 years of experience.
• Snowflake: Hands‑on experience building and optimizing data models, writing advanced SQL (PIVOT, GROUPING SETS, ROLLUP, CUBE), and managing Snowflake environments in production.
• Multisource integration: Proven ability to connect and ingest data from heterogeneous sources, including relational databases, REST APIs, SaaS platforms, and event streams.
• ETL/ELT design: Experience designing normalized schemas and transformation pipelines that produce clean consumption‑ready data models (star/snowflake schema, dimensional modeling).
• Python: Strong proficiency in Python for data engineering tasks, pipeline orchestration, data transformation, API clients, and scripting automation.
• AI agents within Snowflake: Familiarity with Snowflake Cortex LLM functions and agent‑based patterns for building intelligent data‑driven workflows inside the Snowflake ecosystem.
• Backend integration patterns: Practical experience building backend services and integrations using Python, REST APIs, and related tooling (authentication, pagination, error handling, retry logic).

Preferred Qualifications

• PostgreSQL: Working knowledge of PostgreSQL or equivalent RDBMS, including query optimization, indexing, and schema design patterns.
• Go (Golang): Experience building backend services or microservices in Go is a strong differentiator.
• Cloud data infrastructure: Familiarity with Azure or AWS data services (e.g., Azure Data Factory, Event Hubs, S3) as source or orchestration layers.
• Data observability/testing: Experience with data quality frameworks (e.g., dbt tests) or observability tooling (e.g., Great Expectations, Monte Carlo).

Certifications

None specified.