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.
Snowflake Data Engineer
New York, United States
Actively hiring, first seen by us today- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: Hybrid
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingWe are looking for an experienced, hands-on Data Engineer with strong expertise in Fivetran, dbt, Snowflake, and modern cloud data engineering practices.
The role will focus on building scalable ingestion and transformation pipelines, implementing data quality and orchestration patterns, and supporting enterprise data products consumed by analytics and business teams.
What you’ll bring
All qualificationsPreferred experience
- 5+ years of Data Engineering or related experience.
- 4-6 years of experience in data modelling or data analysis.
- 2+ years of hands-on experience with Snowflake and dbt.
- Experience operating within enterprise DEV → QA → PROD SDLC and change-management processes.
Qualification wording
5+ years of Data Engineering or related experience.
Manage data modelling projects. Ensure adherence to policies. Provide strategic guidance. Lead a team. Graduate in Computer Science, Data Science, or a related field. 4-6 years of experience in data modelling or data analysis.
2+ years of hands-on experience with Snowflake and dbt.
Experience operating within enterprise DEV → QA → PROD SDLC and change-management processes.
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 5, 2026today
- Recorded sightings
- 1
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 0
Early. Similar jobs usually come down between day 6 and day 54.
At EXL Service, jobs usually come down by about day 17.
From 11,184 similar postings that came down, and 219 of EXL Service’s. Coming down is not always a hire.
EXL Service is hiring
202 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Takes jobs down at a usual pace
- 4% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Databricks
- dbt
- Fivetran
- S3
- Snowflake
- Terraform
- Airflow
Where the posting names them
Role Overview We are looking for an experienced, hands-on Data Engineer with strong expertise in Fivetran, dbt, Snowflake, and modern cloud data engineering practices. The candidate should also have experience with Python, and familiarity with AI-assisted development tools such as Claude, Cursor, or VS Code-based AI assistants. The role will focus on building scalable ingestion and transformation pipelines, implementing data quality and orchestration patterns, and supporting enterprise data products consumed by analytics and business teams.
- Git / CI/CD – Branching, pull requests, code reviews, and automated deployment workflows. Python Working knowledge of Python is preferred, particularly for data processing, automation, API integrations, file processing, data validation, and operational scripting.
Python Working knowledge of Python is preferred, particularly for data processing, automation, API integrations, file processing, data validation, and operational scripting. Advanced Python development is not required, but candidates should be comfortable reading, troubleshooting, and developing Python-based data engineering utilities.
Working knowledge of Python is preferred, particularly for data processing, automation, API integrations, file processing, data validation, and operational scripting. Advanced Python development is not required, but candidates should be comfortable reading, troubleshooting, and developing Python-based data engineering utilities. AI-Assisted Development
Typical use cases may include: - Developing and troubleshooting SQL, dbt, and Python code. - Code review, refactoring, and debugging.
- Implement dbt testing, source freshness, incremental processing, documentation, and reusable macros. - Develop optimized Snowflake SQL and scalable analytical data models. - Support Snowflake objects, security/RBAC, stages, data sharing, and data-loading patterns.
Strong hands-on experience with: - Snowflake – Advanced SQL, data modeling, performance optimization, RBAC, stages, and data integration patterns. - dbt / dbt Cloud – Models, tests, macros, incremental models, sources, documentation, jobs, and deployment patterns.
- Fivetran – Connector configuration, schema management, sync troubleshooting, monitoring, and ingestion architecture. - SQL – Complex joins, CTEs, window functions, reconciliation, and query optimization. - Git / CI/CD – Branching, pull requests, code reviews, and automated deployment workflows.
Good to Have - Apache Airflow / AWS MWAA for orchestration. - AWS services such as S3, IAM, Lambda, Secrets Manager, and FSx.
- Apache Airflow / AWS MWAA for orchestration. - AWS services such as S3, IAM, Lambda, Secrets Manager, and FSx. - Salesforce, Marketo, and other SaaS integrations.
- Snowpark / Snowpark Container Services (SPCS). - Databricks. - Terraform / Infrastructure as Code.
Core Responsibilities - Design, build, and support end-to-end data pipelines using Fivetran, dbt, and Snowflake. - Configure and manage Fivetran connectors across SaaS applications, databases, APIs, and file-based sources.
- Configure and manage Fivetran connectors across SaaS applications, databases, APIs, and file-based sources. - Develop and maintain dbt models, including staging, intermediate, mart, and publish layers. - Implement dbt testing, source freshness, incremental processing, documentation, and reusable macros.
- Develop and maintain dbt models, including staging, intermediate, mart, and publish layers. - Implement dbt testing, source freshness, incremental processing, documentation, and reusable macros. - Develop optimized Snowflake SQL and scalable analytical data models.
- Snowflake – Advanced SQL, data modeling, performance optimization, RBAC, stages, and data integration patterns. - dbt / dbt Cloud – Models, tests, macros, incremental models, sources, documentation, jobs, and deployment patterns. - Fivetran – Connector configuration, schema management, sync troubleshooting, monitoring, and ingestion architecture.
- 5+ years of Data Engineering or related experience. - 2+ years of hands-on experience with Snowflake and dbt. - Production experience implementing and supporting Fivetran pipelines.
The ideal candidate should be comfortable owning and troubleshooting the complete data lifecycle: Source → Fivetran → Snowflake → dbt The candidate should also be comfortable using Claude through modern development environments such as Cursor or VS Code to improve engineering productivity, troubleshooting, documentation, and code quality.
- Design, build, and support end-to-end data pipelines using Fivetran, dbt, and Snowflake. - Configure and manage Fivetran connectors across SaaS applications, databases, APIs, and file-based sources. - Develop and maintain dbt models, including staging, intermediate, mart, and publish layers.
- dbt / dbt Cloud – Models, tests, macros, incremental models, sources, documentation, jobs, and deployment patterns. - Fivetran – Connector configuration, schema management, sync troubleshooting, monitoring, and ingestion architecture. - SQL – Complex joins, CTEs, window functions, reconciliation, and query optimization.
- 2+ years of hands-on experience with Snowflake and dbt. - Production experience implementing and supporting Fivetran pipelines. - Experience operating within enterprise DEV → QA → PROD SDLC and change-management processes.
- Develop optimized Snowflake SQL and scalable analytical data models. - Support Snowflake objects, security/RBAC, stages, data sharing, and data-loading patterns. - Implement data quality, reconciliation, monitoring, and operational alerting.
- REST API and SFTP/file-based ingestion. - Snowflake Secure Data Sharing. - Snowpark / Snowpark Container Services (SPCS).
- Databricks. - Terraform / Infrastructure as Code. - Data quality and observability frameworks.
Your next step
Complete your application on fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com. The employer’s form will show what is required.
Applying through Oracle Recruiting
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- Each employer sets which files it accepts, so read the note beside the upload field.
Already applied? Track this application
Has EXL Service posted this job before?
Yes. We’ve followed one other Snowflake Data Engineer job there since October 2026. It is still up.
About EXL Service
- People
- About 65,000 in 2025, up 9% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as EXLS.
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
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.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
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.
Job description
Data Engineer – Modern Data Platform
Role Overview
We are looking for an experienced, hands-on Data Engineer with strong expertise in Fivetran, dbt, Snowflake, and modern cloud data engineering practices. The candidate should also have experience with Python, and familiarity with AI-assisted development tools such as Claude, Cursor, or VS Code-based AI assistants.
The role will focus on building scalable ingestion and transformation pipelines, implementing data quality and orchestration patterns, and supporting enterprise data products consumed by analytics and business teams.
Core Responsibilities
- Design, build, and support end-to-end data pipelines using Fivetran, dbt, and Snowflake.
- Configure and manage Fivetran connectors across SaaS applications, databases, APIs, and file-based sources.
- Develop and maintain dbt models, including staging, intermediate, mart, and publish layers.
- Implement dbt testing, source freshness, incremental processing, documentation, and reusable macros.
- Develop optimized Snowflake SQL and scalable analytical data models.
- Support Snowflake objects, security/RBAC, stages, data sharing, and data-loading patterns.
- Implement data quality, reconciliation, monitoring, and operational alerting.
- Troubleshoot production pipelines and perform root-cause analysis across ingestion and transformation layers.
- Participate in Git-based development, CI/CD, code reviews, and DEV/QA/PROD deployments.
- Collaborate with application, infrastructure, security, analytics, and business teams to onboard new data sources.
Required Technical Skills
Strong hands-on experience with:
- Snowflake – Advanced SQL, data modeling, performance optimization, RBAC, stages, and data integration patterns.
- dbt / dbt Cloud – Models, tests, macros, incremental models, sources, documentation, jobs, and deployment patterns.
- Fivetran – Connector configuration, schema management, sync troubleshooting, monitoring, and ingestion architecture.
- SQL – Complex joins, CTEs, window functions, reconciliation, and query optimization.
- Git / CI/CD – Branching, pull requests, code reviews, and automated deployment workflows.
Python
Working knowledge of Python is preferred, particularly for data processing, automation, API integrations, file processing, data validation, and operational scripting.
Advanced Python development is not required, but candidates should be comfortable reading, troubleshooting, and developing Python-based data engineering utilities.
AI-Assisted Development
Familiarity with Claude and AI-assisted development workflows is preferred; deep AI/LLM development experience is not required.
Candidates should be comfortable using tools such as:
- Claude
- Cursor
- VS Code with AI-assisted development capabilities
Typical use cases may include:
- Developing and troubleshooting SQL, dbt, and Python code.
- Code review, refactoring, and debugging.
- Generating unit/data-quality tests.
- Understanding existing codebases and data pipelines.
- Creating technical documentation.
- Accelerating day-to-day data engineering development while following enterprise security and development standards.
Good to Have
- Apache Airflow / AWS MWAA for orchestration.
- AWS services such as S3, IAM, Lambda, Secrets Manager, and FSx.
- Salesforce, Marketo, and other SaaS integrations.
- REST API and SFTP/file-based ingestion.
- Snowflake Secure Data Sharing.
- Snowpark / Snowpark Container Services (SPCS).
- Databricks.
- Terraform / Infrastructure as Code.
- Data quality and observability frameworks.
- Experience modernizing or migrating legacy ETL/integration platforms.
Preferred Experience
- 5+ years of Data Engineering or related experience.
- 2+ years of hands-on experience with Snowflake and dbt.
- Production experience implementing and supporting Fivetran pipelines.
- Experience operating within enterprise DEV → QA → PROD SDLC and change-management processes.
- Experience designing reusable ingestion and transformation patterns.
- Strong production troubleshooting and root-cause analysis skills.
Candidate Profile
We are specifically looking for a hands-on Data Engineer, rather than primarily a BI/reporting developer.
The ideal candidate should be comfortable owning and troubleshooting the complete data lifecycle:
Source → Fivetran → Snowflake → dbt
The candidate should also be comfortable using Claude through modern development environments such as Cursor or VS Code to improve engineering productivity, troubleshooting, documentation, and code quality.
Manage data modelling projects. Ensure adherence to policies. Provide strategic guidance. Lead a team. Graduate in Computer Science, Data Science, or a related field. 4-6 years of experience in data modelling or data analysis.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
New York, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.