Snowflake Data Engineer Jobs
Snowflake Data Engineer jobs are open across fintech, healthcare, retail, and technology, from associate to staff and principal levels, with specializations in data pipeline architecture, cloud data warehouse optimization, and dbt integration. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 43+ Snowflake Data Engineer jobs
APPLY ONLY IF YOU ARE LOCAL TO OHIO
Hiring: Senior Snowflake Data Engineer / Data Architect
Experience: 5+ Years
We are looking for an experienced Senior Snowflake Data Engineer / Data Architect to design, develop, and manage enterprise-level cloud data platforms.
Key Responsibilities:
- Design and develop automated ELT/ETL pipelines using Python, SQL, and Snowflake.
- Implement and manage Medallion Architecture (Bronze, Silver, Gold).
- Build and optimize data warehouses, Lakehouse solutions, and data models.
- Perform data migration from legacy systems to modern cloud platforms.
- Manage data governance, metadata, and data lineage using Alation.
- Develop data quality frameworks, reporting solutions, and BI-ready datasets.
- Document architecture, technical standards, and best practices.
Required Skills:
- 5+ years of experience in Data Engineering, Data Warehousing, or Data Architecture.
- Strong hands-on experience with Snowflake.
- Expert-level SQL and Python skills.
- Experience building automated ELT/ETL pipelines.
- Knowledge of Medallion Architecture and Lakehouse solutions.
- Strong data modeling knowledge (Facts, Dimensions, Star Schema).
- Hands-on experience with Alation Data Catalog.
- Experience with data governance, metadata management, and data lineage.
- Experience with structured and semi-structured data (JSON, APIs).
Preferred Skills:
- Snowpark, Snowflake Streams and Tasks.
- dbt and ER Studio.
- Cloud data architecture and Agile environments.
Education: Bachelor's degree in Computer Science, IT, Data Analytics, or a related field preferred.
Interested candidates can share their updated resumes for consideration.
APPLY ONLY IF YOU ARE LOCAL TO OHIO
Hiring: Senior Snowflake Data Engineer / Data Architect
Experience: 5+ Years
We are looking for an experienced Senior Snowflake Data Engineer / Data Architect to design, develop, and manage enterprise-level cloud data platforms.
Key Responsibilities:
- Design and develop automated ELT/ETL pipelines using Python, SQL, and Snowflake.
- Implement and manage Medallion Architecture (Bronze, Silver, Gold).
- Build and optimize data warehouses, Lakehouse solutions, and data models.
- Perform data migration from legacy systems to modern cloud platforms.
- Manage data governance, metadata, and data lineage using Alation.
- Develop data quality frameworks, reporting solutions, and BI-ready datasets.
- Document architecture, technical standards, and best practices.
Required Skills:
- 5+ years of experience in Data Engineering, Data Warehousing, or Data Architecture.
- Strong hands-on experience with Snowflake.
- Expert-level SQL and Python skills.
- Experience building automated ELT/ETL pipelines.
- Knowledge of Medallion Architecture and Lakehouse solutions.
- Strong data modeling knowledge (Facts, Dimensions, Star Schema).
- Hands-on experience with Alation Data Catalog.
- Experience with data governance, metadata management, and data lineage.
- Experience with structured and semi-structured data (JSON, APIs).
Preferred Skills:
- Snowpark, Snowflake Streams and Tasks.
- dbt and ER Studio.
- Cloud data architecture and Agile environments.
Education: Bachelor's degree in Computer Science, IT, Data Analytics, or a related field preferred.
Interested candidates can share their updated resumes for consideration.
See All 43 Snowflake Data Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Snowflake Data Engineer JobsSnowflake Data Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Consulting & Professional Services
- Distribution & Wholesale
What Employers Look For
The qualifications that appear most often in snowflake data engineer jobs.
- Hands-on experience designing and maintaining Snowflake data warehouses
- Proficiency in SQL and at least one language such as Python or Scala
- Experience building data pipelines with tools like dbt, Airflow, or Spark
- Familiarity with a major cloud platform: AWS, Azure, or Google Cloud
- Understanding of data modeling concepts including star and snowflake schemas
- SnowPro Core certification or equivalent Snowflake platform credential preferred
Tips for Your Snowflake Data Engineer Job Search
Tailor your resume to Snowflake-specific work
Generic data engineering resumes get filtered out fast. Highlight Snowflake-specific contributions: virtual warehouse sizing decisions you made, Snowpipe configurations you built, or cost optimization work you led. Reviewers want to see that you've operated Snowflake at scale, not just queried it.
Show dbt and orchestration tool fluency
Most snowflake data engineer postings pair Snowflake with dbt, Airflow, or a cloud-native orchestrator. If you've built or maintained dbt models on top of Snowflake, name the project, the model count, and the scheduling tool. That combination shortens the recruiter's matching work.
Apply early to roles that fit
Migrate Mate lists snowflake data engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target postings by cloud platform alignment
Snowflake runs on AWS, Azure, and GCP, and many teams want engineers who already know their cloud stack. Filter for openings that name the platform your experience is deepest on. Matching cloud familiarity is a quick screening signal for hiring managers.
Prepare for a SQL and performance take-home
Snowflake data engineer interviews almost always include a hands-on round: writing efficient SQL against a multi-table schema, explaining query execution plans, or diagnosing a slow virtual warehouse. Practice reading the Query Profile in Snowflake's UI before your first technical screen.
Negotiate total compensation, not just base salary
Data engineering offers often include cloud certification reimbursements, remote equipment stipends, and stock. Ask HR to break down each component before you evaluate the offer. Knowing what is variable versus fixed helps you compare roles that look similar on base alone.
Snowflake Data Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most snowflake data engineers?
The most active employers for snowflake data engineers right now are Deloitte, Infosys, and Accenture, and the most openings are in Texas, Ohio, and Illinois, based on current listings on Migrate Mate as of November 2026. Demand is especially concentrated in fintech, healthcare analytics, and cloud-native technology companies.
How many snowflake data engineer jobs are remote?
About 86% of snowflake data engineer openings are fully remote or hybrid as of November 2026, reflecting strong demand for distributed data teams. Pipeline engineering, dbt modeling, and cloud warehouse administration are the sub-specializations most likely to be listed as fully remote, since they depend on cloud tools rather than on-site infrastructure.
How do you become a snowflake data engineer?
Start by building a solid foundation in SQL and data modeling, then get hands-on with Snowflake through its free trial environment. Learn a pipeline orchestration tool like Airflow or dbt, and deploy a small end-to-end project you can discuss in interviews. Earning the SnowPro Core certification signals platform fluency to employers and is widely recognized in job postings.
Can you get a snowflake data engineer job with little experience?
Yes, entry-level snowflake data engineer roles exist, particularly at companies migrating to Snowflake from legacy warehouses who need help with the transition work. Build a portfolio project that shows a full pipeline from raw data ingestion through a Snowflake stage to a dbt-modeled output table. Emphasizing cloud fundamentals and SQL depth compensates for limited professional experience.
What does the snowflake data engineer interview process look like?
Most processes run three to four rounds: a recruiter screen, a technical phone interview covering SQL and data modeling concepts, a hands-on take-home or live coding exercise using Snowflake's query environment, and a final system design round where you walk through how you'd architect a data warehouse for a given use case. Some teams also include a brief culture or cross-functional interview.
Where can I find and apply to snowflake data engineer jobs?
You can find and apply to snowflake data engineer jobs on Migrate Mate, which lists current openings from companies across the United States. Search for roles that match your experience level and specialization, then apply directly to each listing that fits. All the active postings are in one place, so you don't have to check multiple sources.
See All 43 Snowflake Data Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Snowflake Data Engineer Jobs