Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Work setup in the employer’s posting: remoteFrom the employer’s posting
BlueCloud is seeking an experienced Senior Snowflake Data Engineer to design, build, and optimize scalable data solutions within complex enterprise environments.
You will collaborate with data architects, analysts, DevOps engineers, and client stakeholders to deliver secure, maintainable, and high-performing data platforms.
Design, build and maintain scalable data pipelines inside Snowflake
Modernize Python and stored-procedure pipelines with incremental loading
Tune query performance, warehouse sizing and Snowflake costs
Build orchestration, monitoring, error handling and recovery mechanisms
Design dimensional and relational data models
BlueCloud is seeking an experienced Senior Snowflake Data Engineer to design, build, and optimize scalable data solutions within complex enterprise environments. This is a hands-on engineering role focused on developing reliable data pipelines, improving Snowflake performance and cost efficiency, and modernizing existing data-processing workloads.
You will collaborate with data architects, analysts, DevOps engineers, and client stakeholders to deliver secure, maintainable, and high-performing data platforms. The ideal candidate combines strong Snowflake expertise with advanced SQL and Python skills and has experience delivering data solutions in cloud-based enterprise environments.
Design, develop, and maintain scalable data pipelines and transformation workflows within Snowflake.
Modernize existing Python- and stored-procedure-based pipelines using set-based processing, incremental loading, and reusable engineering patterns.
Improve platform performance and cost efficiency through query tuning, warehouse right-sizing, clustering strategies, workload isolation, and auto-suspend and auto-resume policies.
Develop reliable orchestration, dependency management, monitoring, error handling, retry, and recovery mechanisms.
Design and maintain dimensional, relational, and domain-oriented data models.
7+ years of experience in data engineering, including significant hands-on experience with Snowflake.
Strong Python development experience for data processing, automation, and pipeline development.
Hands-on experience with Snowpark and Snowflake-native capabilities such as Dynamic Tables, Streams, and Tasks.
Proven experience designing and supporting scalable ELT/ETL pipelines in production environments.
Strong understanding of Snowflake performance and cost optimization, including warehouse sizing, query profiling, clustering, and workload management.
Experience with data modeling, incremental processing, pipeline orchestration, and dependency management.
Experience with Fivetran, Kafka, Airflow, or similar ingestion and orchestration tools.
Familiarity with Terraform or another infrastructure-as-code platform.
Experience with Snowflake Iceberg Tables or modern lakehouse architectures.
Experience supporting business continuity and disaster recovery strategies.
Open 3 monthsWe first saw this posting 95 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
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$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Day 95
Up longer than most. Similar jobs usually come down between day 5 and day 54.
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BlueCloud is seeking an experienced Senior Snowflake Data Engineer to design, build, and optimize scalable data solutions within complex enterprise environments. This is a hands-on engineering role focused on developing reliable data pipelines, improving Snowflake performance and cost efficiency, and modernizing existing data-processing workloads. You will collaborate with data architects, analysts, DevOps engineers, and client stakeholders to deliver secure, maintainable, and high-performing data platforms. The ideal candidate combines strong Snowflake expertise with advanced SQL and Python skills and has experience delivering data solutions in cloud-based enterprise environments. Key Responsibilities
- Design, develop, and maintain scalable data pipelines and transformation workflows within Snowflake. - Build and optimize ELT/ETL processes using SQL, Python, Snowpark, dbt, and Snowflake-native capabilities. - Modernize existing Python- and stored-procedure-based pipelines using set-based processing, incremental loading, and reusable engineering patterns.
- Build and optimize ELT/ETL processes using SQL, Python, Snowpark, dbt, and Snowflake-native capabilities. - Modernize existing Python- and stored-procedure-based pipelines using set-based processing, incremental loading, and reusable engineering patterns. - Implement Snowflake-native data-processing solutions using Dynamic Tables, Streams, Tasks, and stored procedures.
- Advanced SQL skills, including complex transformations, query optimization, and stored procedure development. - Strong Python development experience for data processing, automation, and pipeline development. - Hands-on experience with Snowpark and Snowflake-native capabilities such as Dynamic Tables, Streams, and Tasks.
- 7+ years of experience in data engineering, including significant hands-on experience with Snowflake. - Advanced SQL skills, including complex transformations, query optimization, and stored procedure development. - Strong Python development experience for data processing, automation, and pipeline development.
- Experience with dbt or a comparable data transformation framework. - Familiarity with at least one major cloud platform: AWS, Azure, or GCP. - Experience with Git, CI/CD, automated testing, and modern software delivery practices.
- Experience with data modeling, incremental processing, pipeline orchestration, and dependency management. - Experience with dbt or a comparable data transformation framework. - Familiarity with at least one major cloud platform: AWS, Azure, or GCP.
- Implement data-quality checks, observability, testing, lineage, and documentation standards. - Integrate data from batch and real-time sources using tools such as Fivetran, Kafka, Airflow, or similar technologies. - Contribute to CI/CD pipelines, infrastructure-as-code practices, and automated deployment processes.
Preferred Qualifications - Experience with Fivetran, Kafka, Airflow, or similar ingestion and orchestration tools. - Familiarity with Terraform or another infrastructure-as-code platform.
- Familiarity with Terraform or another infrastructure-as-code platform. - Experience with Snowflake Iceberg Tables or modern lakehouse architectures. - Exposure to Snowflake Cortex, including Cortex Analyst, Cortex Search, or Cortex LLM functions.
BlueCloud is a Snowflake Elite Partner and the 2026 CoCo Catalyst Snowflake Partner of the Year. We help enterprise organizations move from fragmented legacy systems to unified, AI-ready Snowflake platforms — delivering data migration, engineering, governance, BI & analytics, and AI/ML solutions 40–50% faster than traditional approaches. With 450+ Snowflake consultants, 200+ enterprise transformations under our belt, and a 100% Snowflake focus, we combine advisory-led thinking with AI-powered accelerators to turn months of work into weeks of results. Our clients span Financial Services, Healthcare & Life Sciences, Retail, Manufacturing, Energy, and more — and the outcomes speak for themselves: 97% faster reports, 40% fraud reduction, $1.5M in client savings, and 10× client growth.
BlueCloud is a Snowflake Elite Partner and the 2026 CoCo Catalyst Snowflake Partner of the Year. We help enterprise organizations move from fragmented legacy systems to unified, AI-ready Snowflake platforms — delivering data migration, engineering, governance, BI & analytics, and AI/ML solutions 40–50% faster than traditional approaches. With 450+ Snowflake consultants, 200+ enterprise transformations under our belt, and a 100% Snowflake focus, we combine advisory-led thinking with AI-powered accelerators to turn months of work into weeks of results. Our clients span Financial Services, Healthcare & Life Sciences, Retail, Manufacturing, Energy, and more — and the outcomes speak for themselves: 97% faster reports, 40% fraud reduction, $1.5M in client savings, and 10× client growth. We don't just strategize — we execute.
About the Role BlueCloud is seeking an experienced Senior Snowflake Data Engineer to design, build, and optimize scalable data solutions within complex enterprise environments. This is a hands-on engineering role focused on developing reliable data pipelines, improving Snowflake performance and cost efficiency, and modernizing existing data-processing workloads. You will collaborate with data architects, analysts, DevOps engineers, and client stakeholders to deliver secure, maintainable, and high-performing data platforms. The ideal candidate combines strong Snowflake expertise with advanced SQL and Python skills and has experience delivering data solutions in cloud-based enterprise environments.
Key Responsibilities - Design, develop, and maintain scalable data pipelines and transformation workflows within Snowflake. - Build and optimize ELT/ETL processes using SQL, Python, Snowpark, dbt, and Snowflake-native capabilities.
- Modernize existing Python- and stored-procedure-based pipelines using set-based processing, incremental loading, and reusable engineering patterns. - Implement Snowflake-native data-processing solutions using Dynamic Tables, Streams, Tasks, and stored procedures. - Improve platform performance and cost efficiency through query tuning, warehouse right-sizing, clustering strategies, workload isolation, and auto-suspend and auto-resume policies.
Required Qualifications - 7+ years of experience in data engineering, including significant hands-on experience with Snowflake. - Advanced SQL skills, including complex transformations, query optimization, and stored procedure development.
- Strong Python development experience for data processing, automation, and pipeline development. - Hands-on experience with Snowpark and Snowflake-native capabilities such as Dynamic Tables, Streams, and Tasks. - Proven experience designing and supporting scalable ELT/ETL pipelines in production environments.
- Proven experience designing and supporting scalable ELT/ETL pipelines in production environments. - Strong understanding of Snowflake performance and cost optimization, including warehouse sizing, query profiling, clustering, and workload management. - Experience with data modeling, incremental processing, pipeline orchestration, and dependency management.
- Experience with Snowflake Iceberg Tables or modern lakehouse architectures. - Exposure to Snowflake Cortex, including Cortex Analyst, Cortex Search, or Cortex LLM functions. - Experience supporting business continuity and disaster recovery strategies.
- Experience with Fivetran, Kafka, Airflow, or similar ingestion and orchestration tools. - Familiarity with Terraform or another infrastructure-as-code platform. - Experience with Snowflake Iceberg Tables or modern lakehouse architectures.
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
BlueCloud is a Snowflake Elite Partner and the 2026 CoCo Catalyst Snowflake Partner of the Year. We help enterprise organizations move from fragmented legacy systems to unified, AI-ready Snowflake platforms — delivering data migration, engineering, governance, BI & analytics, and AI/ML solutions 40–50% faster than traditional approaches.
With 450+ Snowflake consultants, 200+ enterprise transformations under our belt, and a 100% Snowflake focus, we combine advisory-led thinking with AI-powered accelerators to turn months of work into weeks of results. Our clients span Financial Services, Healthcare & Life Sciences, Retail, Manufacturing, Energy, and more — and the outcomes speak for themselves: 97% faster reports, 40% fraud reduction, $1.5M in client savings, and 10× client growth.
We don't just strategize — we execute.
BlueCloud is seeking an experienced Senior Snowflake Data Engineer to design, build, and optimize scalable data solutions within complex enterprise environments. This is a hands-on engineering role focused on developing reliable data pipelines, improving Snowflake performance and cost efficiency, and modernizing existing data-processing workloads.
You will collaborate with data architects, analysts, DevOps engineers, and client stakeholders to deliver secure, maintainable, and high-performing data platforms. The ideal candidate combines strong Snowflake expertise with advanced SQL and Python skills and has experience delivering data solutions in cloud-based enterprise environments.
Design, develop, and maintain scalable data pipelines and transformation workflows within Snowflake.
Build and optimize ELT/ETL processes using SQL, Python, Snowpark, dbt, and Snowflake-native capabilities.
Modernize existing Python- and stored-procedure-based pipelines using set-based processing, incremental loading, and reusable engineering patterns.
Implement Snowflake-native data-processing solutions using Dynamic Tables, Streams, Tasks, and stored procedures.
Improve platform performance and cost efficiency through query tuning, warehouse right-sizing, clustering strategies, workload isolation, and auto-suspend and auto-resume policies.
Develop reliable orchestration, dependency management, monitoring, error handling, retry, and recovery mechanisms.
Design and maintain dimensional, relational, and domain-oriented data models.
Implement data-quality checks, observability, testing, lineage, and documentation standards.
Integrate data from batch and real-time sources using tools such as Fivetran, Kafka, Airflow, or similar technologies.
Contribute to CI/CD pipelines, infrastructure-as-code practices, and automated deployment processes.
Work closely with architects and client stakeholders to translate business and technical requirements into production-ready solutions.
Participate in code reviews, technical design discussions, estimation, and Agile delivery activities.
7+ years of experience in data engineering, including significant hands-on experience with Snowflake.
Advanced SQL skills, including complex transformations, query optimization, and stored procedure development.
Strong Python development experience for data processing, automation, and pipeline development.
Hands-on experience with Snowpark and Snowflake-native capabilities such as Dynamic Tables, Streams, and Tasks.
Proven experience designing and supporting scalable ELT/ETL pipelines in production environments.
Strong understanding of Snowflake performance and cost optimization, including warehouse sizing, query profiling, clustering, and workload management.
Experience with data modeling, incremental processing, pipeline orchestration, and dependency management.
Experience with dbt or a comparable data transformation framework.
Familiarity with at least one major cloud platform: AWS, Azure, or GCP.
Experience with Git, CI/CD, automated testing, and modern software delivery practices.
Strong troubleshooting, analytical, and problem-solving skills.
Effective written and verbal communication skills, including the ability to collaborate directly with technical and business stakeholders.
Experience with Fivetran, Kafka, Airflow, or similar ingestion and orchestration tools.
Familiarity with Terraform or another infrastructure-as-code platform.
Experience with Snowflake Iceberg Tables or modern lakehouse architectures.
Exposure to Snowflake Cortex, including Cortex Analyst, Cortex Search, or Cortex LLM functions.
Experience supporting business continuity and disaster recovery strategies.
SnowPro Core or SnowPro Advanced certification.
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