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Popular mid-level data platform role in Hyderabad with broad AWS/Python/Terraform requirements increases competition.
Low because core AWS, PySpark, and data platform skills are broadly transferable across industries.
High due to explicit 6+ years and mandatory AWS, Terraform, PySpark, and data platform requirements.
Architect and manage scalable cloud data infrastructure on AWS including services like S3, EMR, Glue, Lambda, Redshift, EC2, and IAM.
Build, optimize, and maintain robust ETL/ELT data pipelines for batch and streaming data processing using Python and PySpark.
Implement infrastructure as code using Terraform and set up CI/CD pipelines for data engineering workflows, ensuring data quality, security, and high availability.
Minimum 6+ years of experience in data platform engineering or related roles.
Strong expertise in AWS services such as S3, EMR, Glue, Redshift, Lambda, IAM, EC2, and CloudWatch.
Proficiency in Python and PySpark for ETL/ELT development; experience with Terraform for infrastructure as code.
Familiarity with orchestration tools like Airflow, SQL and relational/non-relational databases, version control with Git, and CI/CD pipelines.
Experienced senior engineer capable of owning end-to-end data pipeline architecture and cloud infrastructure management.
Technical operator comfortable with managing large-scale AWS cloud environments and automating infrastructure deployment using Terraform.
Collaborates effectively with data scientists, analysts, and stakeholders to translate data requirements into reliable, secure solutions.