Jobs / New***
Sr. Data Engineer
New*** · United States
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United States140,000-150,000 USD/yearlyRemote
Remuneration
140,000-150,000 USD/yearly
Location
United States
Visa sponsorship
Sponsors visa
Job summary
Overview: Position: Sr. Data Engineer Location: Remote – USA (If living within 31 miles of Santa Ana, CA or Austin, TX will need to be able to work 4 days on-site) Compensation: $140,000–$150,000 DOE - Actual compensation may vary from posting based on geographic location, work experience, education, and/or skill level. Position Summary We are seeking an experienced, hands-on Sr.
Benefits
Compensation: $140,000–$150,000 DOEIncluding health, dental & vision, retirement with company contribution, parentaAnd generous PTO.New American Funding also offers sales incentive pay for most sales roles and anNew American Funding’s compensation andAre subject to change and may be modified in the future.Work Authorization: Must be able to verify identity and employment eligibility t
Qualifications
- Actual compensation may vary from posting based on geographic location, work experience, education, and/or skill level.
- We are seeking an experienced, hands-on Sr.
- into scalable data solutions.
- Troubleshoot complex production issues, perform root cause analysis, and implement long-term solutions to improve platform reliability.
- Evaluate and leverage emerging Snowflake capabilities such as Pipeline Builder, Openflow, Dynamic Tables, Snowpark, Cortex, and other platform innovations to continuously improve the data ecosystem.
- Promote engineering best practices through documentation, knowledge sharing, and mentoring of junior engineers.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- 7+ years of experience designing and developing enterprise ETL/ELT solutions and cloud data warehouse platforms.
- Extensive hands-on experience with Snowflake.
- Strong proficiency in SQL and Python.
- Strong experience designing dimensional and normalized data models and building certified datasets for enterprise consumption.
- Experience designing, developing, and optimizing large-scale, high-volume data pipelines.
Responsibilities
- Design, develop, and maintain scalable, reliable, and high-performance cloud-native data pipelines.
- Develop and optimize enterprise data warehouse architectures, data models, and reusable data engineering frameworks.
- Design and implement dimensional or normalized data models and certified datasets that provide trusted, governed data for analytics, reporting, AI, and operational workloads.
- Build metadata-driven and configuration-driven ETL/ELT frameworks that improve development efficiency, consistency, maintainability, and scalability.
- Implement and enhance Data Quality, Data Observability, monitoring, lineage, and automated alerting capabilities across data pipelines.
- Optimize data pipelines for performance, scalability, reliability, and cost efficiency.
- Establish and follow CI/CD practices, including source control, automated testing, code reviews, and deployment automation.
- Partner with Data Scientists, Analysts, Product Owners, and business stakeholders to translate
- This job profile is not intended to be an all-inclusive list of job
- as one may perform additional related
- as assigned in order to meet the needs of the organization.
- Physical Demands: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job.
Skills
Communication
Degrees
AssociateDegree
Industry
AutomotiveBankingEducationLogistics
Company size
EnterpriseSmb