Senior Data Engineer

Jobot; Austin (TX); On-site; USD 155,000 - 175,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive benefits

Long-term stability

Job summary

A large, global organization is seeking a highly motivated Senior Data Engineer to lead the architecture and deployment of next-generation data-driven platforms. This role bridges Data Science and Production Engineering, ensuring reliable and scalable deployments in the cloud. Key responsibilities include designing data pipelines, developing APIs, and managing infrastructure using GKE. Candidates must have 5+ years of experience in Data Engineering, strong Python and SQL skills, and expertise in GCP technologies. Competitive salary offered.

Qualifications

• 5+ years of professional experience in Data Engineering, Software Engineering, or Cloud Engineering.
• Deep expertise in Python for application development, data processing, and automation.
• Proficient in SQL with experience in relational and analytical data design.

Responsibilities

• Design, build, and maintain robust data ingestion and transformation pipelines.
• Write clean, efficient Python code for automation and infrastructure tooling.
• Design, develop, and deploy high-performance Python APIs.

Skills

Python

SQL

Data orchestration tools (Dagster, Airflow)

Docker

Kubernetes

Tools

GKE

BigQuery

Flask

FastAPI

Job description

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Job Details

Senior Data Engineer at a large, global organization operating at the intersection of technology, data, and digital products.

Salary: $155,000 - $175,000 per year.

About Us

• Competitive salary and comprehensive benefits
• Long-term stability with continued investment in technology and engineering
• High-visibility work with real-world impact
• A collaborative, engineering-driven culture focused on quality and continuous improvement

Why Join Us

• Work on data and machine learning platforms operating at significant scale
• Own and influence core systems that power critical business capabilities
• Collaborate with experienced engineers and data scientists in a highly technical environment
• Tackle complex engineering challenges with modern cloud and MLOps tooling
• Enjoy the stability of a mature organization combined with the opportunity to modernize and innovate

Role Summary

We are seeking a highly motivated Senior Data Engineer to lead the architecture, deployment, and operation of next-generation, data-driven platforms. In this role, you will bridge the gap between Data Science and Production Engineering, ensuring datasets, machine learning models, and core services are deployed reliably, scalably, and securely in the cloud.

Key Responsibilities

• Data Pipeline Design & Orchestration
  • Design, build, and maintain robust data ingestion and transformation pipelines.
  • Leverage modern orchestration tools to ensure reliable, observable data flows supporting machine learning workloads.
• Core Development
  • Write clean, efficient, and well-tested Python code for automation, infrastructure tooling, and service integration.
  • Develop shared libraries and glue services connecting cloud-native components.
• API & Service Deployment
  • Design, develop, and deploy high-performance Python APIs (FastAPI / Flask) to serve machine learning predictions and core application logic.
• MLOps Pipeline Ownership
  • Own end-to-end pipelines for continuous training, deployment, versioning, and monitoring of production ML models (e.g., recommendation or personalization systems).
• Infrastructure Management
  • Architect and maintain scalable, fault-tolerant infrastructure using Kubernetes (GKE) within Google Cloud Platform.
  • Ensure reliability, performance, and cost efficiency across environments.
• Collaboration & Mentorship
  • Partner closely with data scientists, software engineers, and platform teams.
  • Provide technical leadership and mentorship to junior engineers.

Qualifications

Must-Have (Engineering Excellence)

• 5+ years of professional experience in Data Engineering, Software Engineering, or Cloud Engineering.
• Deep expertise in Python for application development, data processing, and automation.
• Proven experience building and deploying production-grade backend services and APIs (FastAPI, Flask, or Django).
• Strong SQL skills with experience designing and optimizing schemas for relational and analytical data stores (e.g., BigQuery, Cloud SQL).
• Hands-on experience with data orchestration tools such as Dagster or Airflow.
• Extensive experience designing and operating services within Google Cloud Platform (BigQuery, Pub/Sub, Vertex AI, Compute Engine).
• Expert-level knowledge of Docker and Kubernetes, including Helm-based deployments.

Nice-to-Have (DevOps & MLOps)

• Experience with Infrastructure as Code tools such as Terraform or Crossplane.
• CI/CD experience using GitHub Actions or similar tooling.
• Familiarity with observability stacks (Prometheus, Grafana, Cloud Logging).
• Understanding of cloud security principles and enterprise compliance requirements.
• Direct experience supporting production MLOps workflows (model monitoring, drift detection, automated retraining).

Next Steps

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