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# Cloud Dataflow Engineer/Analyst

- **Company:** Spatial Front Inc.
- **Location:** New York, NY, United States
- **Experience:** Starter
- **Salary:** $75,000.0 - $110,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Bash Shell, Big Data, Cloud Computing, Cloud Engineering, Information Systems, Databases, Continuous Integration, Data Files, Data Integration, Extract Transform Load (ETL), Data Security, Relational Databases, Perl (Programming Language), Data Flow Control, Revision Control Systems, Monitoring of Systems, Information Lifecycle Management, Python (Programming Language), Linux System Administration, Machine Learning, Nagios, Cloud Services, Software Engineering, SQL Databases, Data Streaming, Subversion, Systems Integration, Scripting, Cloud Platform System, Data Ingestion, System Availability, Git, Information Technology, Deployment Automation, Real Time Data, Api Design, Cloudwatch, Code Restructuring, Software Version Control, Data Pipelines, Legacy Systems
- **Published:** October 31, 2026
- **Apply:** https://www.careerbuilder.com/job-details/cloud-dataflow-engineer-analyst-new-york-ny--5e65e33f-d1f3-4722-a09d-40efc38020e2

## About the Role

Software Engineering, Cloud Computing, Analysis Skills, Data Sets, Software Engineering, Analysis Skills, Cloud Computing, High Availability, Automation, Artificial Intelligence (AI), * 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, * 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

## Description

Spatial Front, Inc. (SFI), a two-time USA Today Top Workplaces awardee and Washington Post Top Workplaces honoree, is seeking a Cloud Dataflow Engineer / Analyst to support a mission-critical enterprise data modernization initiative. In this role, you will join our Dataflow Team to serve as the critical operational bridge moving high-volume, real-time datasets from legacy on-premise infrastructure into a centralized, high-availability cloud platform., Over the next 6-12 months, your primary focus will be supporting the ingestion, automation, and reliability of real-time data streams to power scalable data access, advanced scientific analytics, and future AI/ML capabilities across hybrid environments., 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.