Torque Technologies LLC
Senior Snowflake Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Snowflake Data Engineer in Boston, MA, for a long-term contract. Requires 5+ years of data engineering experience, strong Python and SQL skills, and expertise in dbt Core and OpenFlow. On-site work is mandatory.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
June 18, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Greater Boston
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🧠 - Skills detailed
#Data Science #Azure #Python #Snowflake #AI (Artificial Intelligence) #Monitoring #BI (Business Intelligence) #AWS (Amazon Web Services) #Data Pipeline #GCP (Google Cloud Platform) #dbt (data build tool) #Macros #SQL (Structured Query Language) #Cloud #Datasets #ML (Machine Learning) #Scala #Data Engineering #"ETL (Extract #Transform #Load)" #Observability #Logging #Data Modeling #Deployment #Data Processing #Strategy #Security
Role description
Position: Snowflake Data Engineer
Location: Boston, MA.
Duration: Long Term.
Job Summary
We’re hiring a Senior Snowflake Data Engineer to build and operate reliable, scalable data pipelines and curated data products on the Snowflake Data Cloud. Our platform uses a multi-account strategy, and our primary workloads support BI and ML/AI. This is a hands-on engineering role focused on Python-driven data engineering, robust ETL/ELT, and modern transformation practices using dbt Core and OpenFlow.
You’ll partner with analytics, data science, platform, and security teams to deliver production-grade datasets with strong quality, observability, governance alignment, and performance/cost efficiency.
Required Qualifications
• 5+ years of data engineering experience, including significant delivery on Snowflake in production.
• Strong Python skills (clean, testable code; packaging; logging/metrics; performance-aware data processing).
• Strong SQL and data modeling fundamentals (dimensional and/or domain-oriented modeling).
• Hands-on experience with dbt Core (models, macros, tests, docs, deployments, CI practices).
• Hands-on experience with OpenFlow (building/running flows, operational support, troubleshooting).
• Proven experience designing and operating ETL/ELT pipelines (incremental loads, CDC concepts, error handling, and backfills).
• Experience working in cloud environments (AWS/Azure/GCP) and production operations (monitoring, on-call/incident response, SLAs).
• Comfortable working across teams (analytics, ML, platform/security) and translating requirements into deliverable datasets.
Position: Snowflake Data Engineer
Location: Boston, MA.
Duration: Long Term.
Job Summary
We’re hiring a Senior Snowflake Data Engineer to build and operate reliable, scalable data pipelines and curated data products on the Snowflake Data Cloud. Our platform uses a multi-account strategy, and our primary workloads support BI and ML/AI. This is a hands-on engineering role focused on Python-driven data engineering, robust ETL/ELT, and modern transformation practices using dbt Core and OpenFlow.
You’ll partner with analytics, data science, platform, and security teams to deliver production-grade datasets with strong quality, observability, governance alignment, and performance/cost efficiency.
Required Qualifications
• 5+ years of data engineering experience, including significant delivery on Snowflake in production.
• Strong Python skills (clean, testable code; packaging; logging/metrics; performance-aware data processing).
• Strong SQL and data modeling fundamentals (dimensional and/or domain-oriented modeling).
• Hands-on experience with dbt Core (models, macros, tests, docs, deployments, CI practices).
• Hands-on experience with OpenFlow (building/running flows, operational support, troubleshooting).
• Proven experience designing and operating ETL/ELT pipelines (incremental loads, CDC concepts, error handling, and backfills).
• Experience working in cloud environments (AWS/Azure/GCP) and production operations (monitoring, on-call/incident response, SLAs).
• Comfortable working across teams (analytics, ML, platform/security) and translating requirements into deliverable datasets.
