Position Summary

We are seeking an Experienced Data Engineer with strong expertise in cloud-native data platforms, DevOps, and modern data engineering practices. This role is responsible for designing, building, and maintaining scalable data pipelines, cloud infrastructure, and CI/CD processes that power analytics, machine learning, and enterprise applications.

The ideal candidate is passionate about automation, infrastructure-as-code, cloud architecture, and delivering reliable, high-performance data solutions. You will work closely with software engineers, data scientists, architects, and business stakeholders to build secure, scalable, and resilient data platforms.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines for batch and real-time processing.
• Build and optimize cloud-based data platforms using services such as AWS, Azure, or Google Cloud.
• Implement CI/CD pipelines to automate deployment, testing, and monitoring of data infrastructure.
• Develop Infrastructure as Code (IaC) using Terraform, CloudFormation, or similar technologies.
• Design and manage data lakes, data warehouses, and lakehouse architectures.
• Build and maintain ETL/ELT processes using modern orchestration tools.
• Monitor data quality, reliability, and pipeline performance.
• Implement logging, monitoring, alerting, and observability across data platforms.
• Collaborate with DevOps and Security teams to ensure infrastructure meets security and compliance standards.
• Optimize cloud resource utilization and control infrastructure costs.
• Support disaster recovery, backup, and high-availability strategies.
• Partner with data analysts, BI developers, and data scientists to deliver trusted datasets.
• Document architecture, deployment processes, and operational procedures.
• Stay current with emerging cloud, DevOps, and data engineering technologies.
   

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (or equivalent experience).
• 5+ years of experience in Data Engineering or Cloud Engineering.
• Strong experience with cloud platforms:
  • AWS
  • Microsoft Azure
  • Google Cloud Platform (GCP)
• Experience building production-grade data pipelines.
• Strong SQL skills.
• Experience with Python, Scala, or Java.
• Experience with Spark or distributed data processing frameworks.
• Experience with containerization technologies such as Docker.
• Experience with Kubernetes or container orchestration.
• Hands-on experience implementing CI/CD pipelines.
• Experience using Git-based source control.
• Experience with Infrastructure as Code:
  • Terraform
  • CloudFormation
  • ARM/Bicep
• Experience with data orchestration tools such as:
  • Apache Airflow
  • Azure Data Factory
  • Prefect
  • Dagster
• Experience with relational and NoSQL databases.
• Strong understanding of data modeling and data architecture.
• Familiarity with security best practices including IAM, encryption, and secrets management.