Data Engineer III

• Build and maintain scalable data pipelines and architectures on cloud platforms, primarily AWS
• Develop, test, and deploy high-quality data and backend solutions with a focus on reliability and performance
• Design and implement microservices and APIs to support data workflows and integrations
• Optimize data processing systems to handle large-scale datasets efficiently and ensure high availability
• Implement data solutions using distributed processing frameworks such as Spark or PySpark
• Apply Agile and DevOps practices, including CI/CD, automation, and infrastructure as code
• Collaborate with stakeholders to understand data requirements and improve data accessibility and usability
• Ensure data quality, integrity, and consistency across systems and platforms
• Support integration of data into analytics and reporting platforms for business insights
• Contribute to building resilient, secure, and scalable systems aligned with engineering best practices

Required qualifications, capabilities, and skills:

• Bachelor’s degree in Computer Science, Engineering, or a related discipline
• Hands-on experience in data engineering or backend software engineering
• Strong programming skills in Python with experience in data processing frameworks such as Spark or PySpark
• Experience building and maintaining data pipelines and large-scale data systems (data lake or warehouse environments)
• Knowledge of SQL and experience working with structured and unstructured datasets
• Experience with distributed systems and scalable data architectures
• Familiarity with CI/CD practices, Agile methodologies, and application resiliency
• Experience with data tools such as dbt, Glue, or Trino
• Exposure to orchestration tools such as Airflow or Step Functions and experience with infrastructure as code

Preferred qualifications, capabilities, and skills:

• Experience with containerization technologies such as Docker and Kubernetes
• Understanding of cloud platforms, preferably AWS
• Knowledge of streaming and real-time data processing (Kafka, Spark Streaming)
• Experience building automated testing frameworks across unit, integration, and end-to-end levels
• Exposure to modern frontend technologies such as TypeScript or React
  • Cloud certifications in AWS (e.g., Data Engineer or Solutions Architect)