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.
Senior Data Engineer
Dallas, TX, USA; Houston, TX, USA; Charlotte, NC, USA
Live, first seen by us 61 days ago- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign, build and manage data transformations in dbt
Document source-to-target mappings with data team members
Optimize Snowflake performance and monitor data workflows
Develop testing frameworks to validate data solutions
Provide technical support for data warehouse processing
From the employer’s posting
Design, build, and manage data transformations in dbt.
Work with data team members to analyze source data and identify transformation requirements
Develop and enhance monitoring of workflows and processes.
Develop testing frameworks for solutions to ensure that solutions meet requirements and perform as expected.
Provide comprehensive technical support for data warehouse processing.
What you’ll bring
All qualificationsCore experience
- 5+ years developing and scaling dbt projects
- 5+ years of experience with Snowflake
- Experience with data pipeline tools like Fivetran
- Expert in SQL and data analysis
- Proven experience designing and managing security requirements
Preferred experience
- Experience with Python and AI
- Familiarity with Azure and cloud architectures
Qualification wording
Minimum 5+ years of experience developing and scaling dbt projects.
Minimum 5+ years of experience with Snowflake.
Experience working with data pipeline tools like Fivetran.
Expert in SQL and data analysis.
Proven experience designing and managing security requirements.
Experience with Python and AI.
Familiarity with Azure and cloud architectures.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 4, 202661 days ago
- Recorded sightings
- 125
- Last seen by us
- Nov 5, 2026
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 61
Up longer than most. Similar jobs usually come down between day 6 and day 54.
From 11,069 similar postings that came down. Coming down is not always a hire.
Flow Control Group is hiring
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee 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
- Azure
- dbt
- Fivetran
- Snowflake
Where the posting names them
Additional Technical Skills: Expert in SQL and data analysis. Experience with Python and AI. Strong understanding of data integrations, data warehousing, data modeling, and data engineering. Expert at creating architecture diagrams and documenting requirements and design details. Familiarity with Azure and cloud architectures. Required Analytical Skills:
FCG is seeking a Senior Data Engineer to work on our Central Data Platform team, utilizing Snowflake, dbt, and Fivetran, and responsible for end-to-end ELT development from ingestion of raw source system data through our integrated and data consumption layers in Snowflake. This role provides data analysis of raw and transformed data, documents source-to-target mappings, provides Snowflake platform expertise, develops and tests data transformations in dbt, and continues to evolve our dbt and Snowflake environments, including architecture, performance tuning, job monitoring, troubleshooting, and environment management. The Senior Data Engineer works as part of a multi-functional team of data professionals focused on delivering data and evolving our technical infrastructure and processes to help deliver reliable, quality data to our business stakeholders. Key Responsibilities: Technical Expertise: Provide technical expertise in all capabilities of dbt and Snowflake. Development: Design, build, and manage data transformations in dbt. Create reusable components and templates and proof-of-concept solutions. Develop and manage data pipelines as needed. Implement functionality in Snowflake. Source to Target Mappings: Work with data team members to analyze source data and identify transformation requirements to move data to our data warehouse and data marts. Data Integration: Design robust, reliable, scalable, and performant systems for large-volume data processing. Help drive decisions on data architecture and engineering best practices. Data Observability: Develop and enhance monitoring of workflows and processes. Solution Design: Collaborate with technical teams to design and implement solutions that meet business requirements and align with best practices. Security: Design security standards and ensure proper implementation of security. Performance: Ensure our data warehouse processing is optimized for performance. Collaborate with team members to ensure data loads and transformations flow through the system to deliver data according to requirements. Support: Provide comprehensive technical support for data warehouse processing. Testing and Validation: Develop testing frameworks for solutions to ensure that solutions meet requirements and perform as expected. Metadata: Work with business users, technical teams, and data stewards to create documentation and metadata to support understanding of data warehouse processing. Continuous Improvement: Identify opportunities for process improvements and system enhancements to increase efficiency and effectiveness.
FCG is seeking a Senior Data Engineer to work on our Central Data Platform team, utilizing Snowflake, dbt, and Fivetran, and responsible for end-to-end ELT development from ingestion of raw source system data through our integrated and data consumption layers in Snowflake. This role provides data analysis of raw and transformed data, documents source-to-target mappings, provides Snowflake platform expertise, develops and tests data transformations in dbt, and continues to evolve our dbt and Snowflake environments, including architecture, performance tuning, job monitoring, troubleshooting, and environment management. The Senior Data Engineer works as part of a multi-functional team of data professionals focused on delivering data and evolving our technical infrastructure and processes to help deliver reliable, quality data to our business stakeholders. Key Responsibilities: Technical Expertise: Provide technical expertise in all capabilities of dbt and Snowflake. Development: Design, build, and manage data transformations in dbt. Create reusable components and templates and proof-of-concept solutions. Develop and manage data pipelines as needed. Implement functionality in Snowflake. Source to Target Mappings: Work with data team members to analyze source data and identify transformation requirements to move data to our data warehouse and data marts. Data Integration: Design robust, reliable, scalable, and performant systems for large-volume data processing. Help drive decisions on data architecture and engineering best practices. Data Observability: Develop and enhance monitoring of workflows and processes. Solution Design: Collaborate with technical teams to design and implement solutions that meet business requirements and align with best practices. Security: Design security standards and ensure proper implementation of security. Performance: Ensure our data warehouse processing is optimized for performance. Collaborate with team members to ensure data loads and transformations flow through the system to deliver data according to requirements. Support: Provide comprehensive technical support for data warehouse processing. Testing and Validation: Develop testing frameworks for solutions to ensure that solutions meet requirements and perform as expected. Metadata: Work with business users, technical teams, and data stewards to create documentation and metadata to support understanding of data warehouse processing. Continuous Improvement: Identify opportunities for process improvements and system enhancements to increase efficiency and effectiveness. Qualifications:
Experience: Minimum 5+ years of experience developing and scaling dbt projects. Minimum 5+ years of experience with Snowflake. Proven experience designing and implementing dbt transformations in large-scale enterprise analytics environments. Deep knowledge of all aspects of the Snowflake environment, from databases to security and AI capabilities. Experience working with data pipeline tools like Fivetran. Proven experience designing and managing security requirements. Experience in supporting data engineering applications. Minimum of 5 years working with cross-functional teams and managing multiple projects and priorities. Additional Technical Skills:
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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
FCG is seeking a Senior Data Engineer to work on our Central Data Platform team, utilizing Snowflake, dbt, and Fivetran, and responsible for end-to-end ELT development from ingestion of raw source system data through our integrated and data consumption layers in Snowflake. This role provides data analysis of raw and transformed data, documents source-to-target mappings, provides Snowflake platform expertise, develops and tests data transformations in dbt, and continues to evolve our dbt and Snowflake environments, including architecture, performance tuning, job monitoring, troubleshooting, and environment management. The Senior Data Engineer works as part of a multi-functional team of data professionals focused on delivering data and evolving our technical infrastructure and processes to help deliver reliable, quality data to our business stakeholders.
Key Responsibilities:
Technical Expertise: Provide technical expertise in all capabilities of dbt and Snowflake.
Development: Design, build, and manage data transformations in dbt. Create reusable components and templates and proof-of-concept solutions. Develop and manage data pipelines as needed. Implement functionality in Snowflake.
Source to Target Mappings: Work with data team members to analyze source data and identify transformation requirements to move data to our data warehouse and data marts.
Data Integration: Design robust, reliable, scalable, and performant systems for large-volume data processing. Help drive decisions on data architecture and engineering best practices.
Data Observability: Develop and enhance monitoring of workflows and processes.
Solution Design: Collaborate with technical teams to design and implement solutions that meet business requirements and align with best practices.
Security: Design security standards and ensure proper implementation of security.
Performance: Ensure our data warehouse processing is optimized for performance. Collaborate with team members to ensure data loads and transformations flow through the system to deliver data according to requirements.
Support: Provide comprehensive technical support for data warehouse processing.
Testing and Validation: Develop testing frameworks for solutions to ensure that solutions meet requirements and perform as expected.
Metadata: Work with business users, technical teams, and data stewards to create documentation and metadata to support understanding of data warehouse processing.
Continuous Improvement: Identify opportunities for process improvements and system enhancements to increase efficiency and effectiveness.
Qualifications:
Experience:
Minimum 5+ years of experience developing and scaling dbt projects.
Minimum 5+ years of experience with Snowflake.
Proven experience designing and implementing dbt transformations in large-scale enterprise analytics environments.
Deep knowledge of all aspects of the Snowflake environment, from databases to security and AI capabilities.
Experience working with data pipeline tools like Fivetran.
Proven experience designing and managing security requirements.
Experience in supporting data engineering applications.
Minimum of 5 years working with cross-functional teams and managing multiple projects and priorities.
Additional Technical Skills:
Expert in SQL and data analysis.
Experience with Python and AI.
Strong understanding of data integrations, data warehousing, data modeling, and data engineering.
Expert at creating architecture diagrams and documenting requirements and design details.
Familiarity with Azure and cloud architectures.
Required Analytical Skills:
Excellent problem-solving skills and attention to detail.
Ability to analyze complex business processes and translate them into technical requirements.
Evaluate performance, traceability, and usability in all designs.
Expertise working to implement data warehouses, data marts, and analytic datasets that align with business objectives.
Ability to analyze data from disparate sources to identify gaps in data or definitions.
Ability to effectively test data products and analyze data by looking for patterns and anomalies in the data that impact deliverables.
Ensure alignment with data standards and data governance.
Communication Skills:
Strong verbal and written communication skills.
Ability to effectively communicate with technical and non-technical stakeholders.
Personal Attributes:
Team Player: Ability to work collaboratively in a team environment.
Adaptability: Comfortable working in a fast-paced and dynamic environment.
Self-Motivated: Proactive and able to work independently with minimal supervision.
Customer Focus: Strong commitment to delivering high-quality service to internal and external customers.
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Dallas, TX, USA; Houston, TX, USA; Charlotte, NC, USA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.