Real-Time Cloud Dataflow Engineer – Data Ingestion

Spatial Front, Inc.; Washington, Northern (District of Columbia, KY); Hybrid; USD 75,000 - 110,000; Full time

Benefits offered by this job

Comprehensive benefits package

Equal Opportunity Employer

Job summary

Spatial Front, Inc. (SFI) is seeking a Cloud Dataflow Engineer / Analyst to support a mission-critical data modernization initiative.

You will join the Dataflow Team to move high-volume, real-time datasets from legacy on-premise systems into a cloud platform with high availability. Over the next 6-12 months, you will focus on ingestion, automation, and reliability of real-time data streams to enable scalable data access, advanced analytics, and future AI/ML capabilities across hybrid

Qualifications

• Bachelor’s degree or equivalent experience in CS/IS or related field.
• 1–2 years hands-on cloud platform experience (AWS/Azure/GCP).
• 2+ years Linux/Unix administration or engineering support.
• Strong Python and Bash scripting; solid SQL and relational DB fundamentals.
• Experience supporting ETL pipelines, data integration, and automated CI/CD deployments.
• At least one foundational or associate-level cloud certification (e.g., AWS Cloud Practitioner).
• Ability to obtain and maintain a Public Trust clearance.

Responsibilities

• Execute large-scale data ingestion and migration from on-prem to cloud environments (AWS/Azure/GCP).
• Refactor legacy dataflow pipelines into automated, API-driven workflows using Python and Bash.
• Maintain and migrate legacy scripts to scalable, cloud-native solutions.
• Support 24/7 on-call rotation for mission-critical data flows.

Skills

Python

Bash

SQL

CI/CD

Cloud platforms

Linux

Education

Bachelor’s degree in Computer Science

Tools

Git

SVN

Job description

Spatial Front, Inc. (SFI) is seeking a Cloud Dataflow Engineer / Analyst to support a mission-critical data modernization initiative.

You will join the Dataflow Team to move high-volume, real-time datasets from legacy on-premise systems into a cloud platform with high availability. Over the next 6-12 months, you will focus on ingestion, automation, and reliability of real-time data streams to enable scalable data access, advanced analytics, and future AI/ML capabilities across hybrid