Design, develop, and maintain efficient ETL pipelines using Python, SQL, AWS Glue, and Redshift.
Automate data flows and integrations using AWS Lambda and other serverless services.
Propose and implement improvements to existing pipelines for better performance, scalability, and maintainability.
Collaborate on designing scalable, resilient data architectures in AWS.
Manage infrastructure as code using Terraform.
Participate in code reviews and use Git for collaborative version control.
Document technical solutions and promote data engineering best practices.
Technical Requirements :
Python : 3+ years (intermediate to advanced level).
SQL : 3+ years, strong with complex data models.
Big Data / PySpark : 12+ years (preferred).
AWS (Lambda, Glue, Redshift, S3) : 23 years hands-on.
Terraform : 12 years (intermediate).
Git : Daily use in collaborative environments.
Strong focus on automation, error handling, logging, and testing in data pipelines.
Professional Profile :
Proactive and improvement-driven mindset.
Analytical thinker with strong problem-solving skills.
Great communicator with technical and non-technical teams.
Strong documentation habits.
Nice to Have :
Experience with CloudWatch or other monitoring tools.
Knowledge of event-driven architectures.
Familiarity with Apache Airflow or other orchestration tools.
Background in FinTech or handling financial data.
AWS certifications are a 6+ years.
(ref : hirist.tech)
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Big Data Developer • Coimbatore
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