Cloud Dataflow Engineer/Analyst

Key Responsibilities

Data Pipeline & Cloud Ingestion

• Execute and streamline large-scale data ingestion and migration processes from legacy on-premise systems to cloud environments (AWS/Azure/GCP).
• Transition legacy dataflow pipelines into automated, API-driven workflows using Python, Bash, and modern CI/CD practices.
• Maintain, refactor, and migrate legacy scripts and tools (Bash, Perl, SQL) to scalable, cloud-native solutions.
• This role offers a unique opportunity to learn the foundational legacy systems of the National Weather Service while simultaneously building the "Gold Standard" of cloud-based weather data dissemination. 

Operations, Monitoring & Reliability

• Ensure continuous, low-latency delivery of mission-critical, high-volume data streams in a 24/7 operational environment.
• Monitor, troubleshoot, and optimize data routing applications, ingestion processes, and underlying cloud services.
• Serve as a Tier 2 technical escalation point for complex data ingestion, formatting, and delivery issues.
• Participate in a 24/7 on-call rotation to support mission-critical availability.

Data Lifecycle & System Integration

• Manage end-to-end data flow operations, including validation, quality control, archival, and retrieval.
• Collaborate with internal engineering teams and external stakeholders to resolve data access, formatting, and integration challenges.
• Author and maintain technical documentation, standard operating procedures (SOPs), and configuration standards.

Education & Experience

• Bachelor’s degree in Computer Science, Information Systems, or related field (or equivalent experience)
• Cloud Infrastructure: 1–2 years of hands-on experience with cloud platforms (AWS, Azure, or GCP).
• Linux Administration: 2+ years of Linux/Unix system administration or engineering support experience.
• Scripting & Databases: Strong proficiency in Python and Bash scripting, alongside solid SQL experience and relational database fundamentals.
• Pipelines & CI/CD: Demonstrated experience supporting ETL pipelines, data integration workflows, and automated CI/CD deployment tools.
• Certification: At least one (1) active foundational or associate-level cloud certification (e.g., AWS Certified Cloud Practitioner or equivalent). 
• Ability to obtain and maintain a Public Trust clearance

Desired Skills & Qualifications

• Domain Expertise: Experience with scientific or meteorological data dissemination systems (NOAA, NASA, DoD) and familiarity with data formats such as METAR, TAF, GRIB, and BUFR.
• System Monitoring: Hands-on experience with monitoring tools (e.g., Big Brother, Nagios) or cloud-native monitoring solutions (e.g., AWS CloudWatch).
• Legacy Tools: Experience with Perl for legacy script migration.
• Version Control: Proficiency with Git, SVN, or similar version control tools.
• Advanced Certifications: Associate or Professional-level cloud engineering certifications 

Additional Information:

• Clearance: Must be authorized to work in the U.S. and be able to obtain and keep a public trust clearance
• Background checks may include Criminal History, Education Verification, Employment Verification, Professional Certifications, and Credit History. (Public Trust investigations typically take 4–8 weeks and require fingerprinting.)
• Work Environment: Hybrid
• Salary Range: $75,000 – $110,000 annually
• Benefits: SFI offers a comprehensive benefits package. Details available at SFI Careers.
• This is a full-time, W2 position.
• No agencies, third parties, or Corp-to-Corp submissions.
• Spatial Front Inc. is an Equal Opportunity Employer — all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status.
• SFI participates in E-Verify.