Data Engineer

Data Engineer (Infrastructure as Code - IaC)

About the Role

We are seeking experienced Data Engineers with strong expertise in Infrastructure as Code (IaC), Python, SQL, and AWS Cloud Services. The ideal candidate will be responsible for developing scalable data pipelines, managing cloud-based data platforms, and automating infrastructure deployment using modern IaC practices.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
• Build and optimize data solutions on AWS cloud platforms.
• Implement and manage Infrastructure as Code (IaC) solutions for cloud environments.
• Develop automation scripts and frameworks using Python.
• Write complex SQL queries, optimize database performance, and ensure data quality.
• Collaborate with data architects, data scientists, and business stakeholders to deliver robust data solutions.
• Monitor, troubleshoot, and optimize cloud infrastructure and data workflows.
• Ensure security, governance, and best practices across cloud and data platforms.
• Participate in code reviews, design discussions, and CI/CD implementation.

Required Skills

• 4-10 years of experience in Data Engineering.
• Strong hands-on experience with Python and SQL.
• Experience with AWS Services
• Strong expertise in Infrastructure as Code (IaC) tools such as:
• Terraform
• AWS CloudFormation
• CDK (preferred)
• Experience building and managing data pipelines and data lakes.
• Knowledge of CI/CD tools and deployment automation.
• Understanding of cloud security and performance optimization.

Preferred Skills

• Experience with Apache Airflow or other orchestration tools.
• Knowledge of Spark, PySpark, or Databricks.
• Experience with containerization technologies such as Docker and Kubernetes.
• Exposure to Agile/Scrum methodologies.
• AWS Certification is a plus.

What We're Looking For

• Strong problem-solving and analytical skills.
• Excellent communication and stakeholder management abilities.
• Ability to work in a fast-paced, cloud-first environment.
• Passion for automation, scalability, and modern data engineering practices.