

AceStack
Snowflake Data Engineer W/ GenAi or AI/ML : Dallas, TX (Hybrid) : Contract/FTE Both
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Snowflake Data Engineer in Dallas, TX (Hybrid), offering $55-60/hr or $115-130k with 10% QPLC. Requires 10+ years of experience, expertise in Snowflake, data governance, and familiarity with AI/ML in financial services.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
480
-
🗓️ - Date
May 7, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
Hybrid
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Dallas, TX
-
🧠 - Skills detailed
#Collibra #Data Ingestion #Snowflake #Metadata #Scala #Data Quality #SQL (Structured Query Language) #Cloud #Migration #Data Engineering #Data Pipeline #Data Governance #ML (Machine Learning) #"ETL (Extract #Transform #Load)" #Data Architecture #Data Management #AI (Artificial Intelligence)
Role description
Job Title: Snowflake Data Engineer
Location: Dallas, TX (Hybrid)
Contract/Fulltime Both
$55-60/hr
$115-130k + 10% QPLC + Benefits
Senior Engineer (10+ years) with some experience in AI/ML or Gen AI.
Job Summary:
We are seeking a Snowflake Data Engineer with strong experience in building semantic layers and implementing native data ingestion patterns on Snowflake. The role focuses on designing scalable, high-performance data pipelines using Snowflake-native capabilities. Exposure to data governance and AI-driven solutions is a plus. This is an individual contributor role supporting a critical data transformation initiative.
Key Responsibilities:
Design and implement Snowflake-based semantic layers to support analytics and business consumption.
Develop and manage data ingestion pipelines using Snowflake Streams, Tasks, and native features.
Collaborate with data architects and business stakeholders to align data models with domain requirements.
Ensure data quality, performance optimization, and adherence to governance standards.
Required Skills:
Strong hands-on experience with Snowflake, including Streams, Tasks, and performance tuning.
Proven expertise in building semantic layers and data models for analytics use cases.
Solid understanding of data engineering concepts, ETL/ELT patterns, and SQL.
Basic familiarity with data governance tools such as Collibra.
Preferred Qualifications:
Exposure to AI/ML or GenAI-driven data use cases within modern data platforms.
Experience working in financial services or regulated data environments.
Knowledge of data governance, metadata management, and lineage concepts.
Prior experience in large-scale data transformation or cloud migration programs.
Job Title: Snowflake Data Engineer
Location: Dallas, TX (Hybrid)
Contract/Fulltime Both
$55-60/hr
$115-130k + 10% QPLC + Benefits
Senior Engineer (10+ years) with some experience in AI/ML or Gen AI.
Job Summary:
We are seeking a Snowflake Data Engineer with strong experience in building semantic layers and implementing native data ingestion patterns on Snowflake. The role focuses on designing scalable, high-performance data pipelines using Snowflake-native capabilities. Exposure to data governance and AI-driven solutions is a plus. This is an individual contributor role supporting a critical data transformation initiative.
Key Responsibilities:
Design and implement Snowflake-based semantic layers to support analytics and business consumption.
Develop and manage data ingestion pipelines using Snowflake Streams, Tasks, and native features.
Collaborate with data architects and business stakeholders to align data models with domain requirements.
Ensure data quality, performance optimization, and adherence to governance standards.
Required Skills:
Strong hands-on experience with Snowflake, including Streams, Tasks, and performance tuning.
Proven expertise in building semantic layers and data models for analytics use cases.
Solid understanding of data engineering concepts, ETL/ELT patterns, and SQL.
Basic familiarity with data governance tools such as Collibra.
Preferred Qualifications:
Exposure to AI/ML or GenAI-driven data use cases within modern data platforms.
Experience working in financial services or regulated data environments.
Knowledge of data governance, metadata management, and lineage concepts.
Prior experience in large-scale data transformation or cloud migration programs.






