Python Data Engineer

We are looking for an experienced and driven Python Data Engineer with 2-9 years of hands-on experience in building and maintaining data pipelines, automating data workflows, and working with cloud infrastructure. The ideal candidate will have a strong background in Python, AWS, PL/SQL, ETL frameworks, and workflow orchestration, along with a good command of scripting, infrastructure automation, and monitoring tools. This is an excellent opportunity to be part of a high-impact team, contributing to the design and execution of scalable and secure data solutions that support strategic business needs.

Responsibilities

• Design, implement, and maintain scalable and efficient ETL/ELT pipelines using Python and AWS services.
• Develop and optimize complex PL/SQL queries, stored procedures, and database objects.
• Create and manage workflow orchestration using Apache Airflow and Autosys.
• Automate infrastructure provisioning with Terraform and manage secrets with Vault.
• Develop system-level scripts using Perl and Shell to support data and platform operations.
• Integrate APIs and services using OpenAPI standards for seamless data flows.
• Monitor system performance, data workflows, and job reliability using Datadog.
• Use GitLab for source control and CI/CD processes to maintain code quality and deployment automation.
• Collaborate with data scientists, analysts, and DevOps teams to ensure robust and secure data infrastructure.
• Identify and troubleshoot bottlenecks in data pipelines and continuously improve reliability and scalability.

Qualifications

Bachelor’s degree or master’s degree in computer science, Engineering, Software Engineering or a Relevant Field.

Required Skills

• Experience: 2–9 years in a Data Engineering or similar backend data role.
• Languages: Proficiency in Python, Shell, and Perl.
• Cloud Expertise: Hands-on experience with AWS (S3, Lambda, Glue, EC2, RDS, etc.).
• Data & ETL: Strong background in ETL/ELT processes, data modeling, and performance tuning.
• Database: Deep understanding of PL/SQL and relational database systems.
• Monitoring & Observability: Practical experience with Datadog.
• Orchestration Tools: Familiarity with Airflow and Autosys for job scheduling.
• API Development: Experience working with or consuming APIs using OpenAPI specifications.
• Infrastructure-as-Code: Working knowledge of Terraform and Vault for IaC and secrets management.
• Version Control & CI/CD: Experience with GitLab or similar version control and CI/CD tools.
• Experience in large-scale, distributed data systems and data pipeline performance optimization.
• Exposure to DevOps practices and cloud-native development environments.
• Strong problem-solving, troubleshooting, and analytical skills.
• Ability to work independently while collaborating in a team-oriented environment.

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