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Open nowPosted 6 days ago

AWS Glue Python Developer

Workable (global search)108,016 open roles

Where
Bengaluru, KA, India
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Your applicationOpen nowAWS Glue Python DeveloperWorkable (global search) · Bengaluru, KA, India

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The clock on this job

Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 6 days ago

Workable (global search) median: 7 days open

The posting

We are seeking an experienced AWS Glue Python Developer to design, develop, and support scalable cloud-based inbound and outbound file based data integration and processing solutions. The ideal candidate will have strong expertise in Python, AWS Glue, PySpark, and serverless AWS services.

The candidate will work with business and technical teams to develop reliable data processing workflows using services such as Amazon S3, EventBridge, Lambda, SNS, SQS, CloudWatch, IAM, and AWS Step Functions or Glue Workflows.

Key Responsibilities

Design and develop inbound and outbound file processing using AWS Glue, Python, and PySpark.

Develop reusable Python modules, utilities, and frameworks for data ingestion, validation, transformation, and error handling.

Build batch inbound and outbound file processing using Amazon S3 and AWS Glue.

Configure Amazon EventBridge rules for scheduling and event-based processing.

Develop AWS Lambda functions for lightweight processing, automation, validation, and integration activities.

Implement messaging and notification solutions using Amazon SNS and Amazon SQS.

Configure Amazon CloudWatch logs, metrics, dashboards, and alarms for operational monitoring.

Develop workflows using AWS Glue Workflows, AWS Step Functions, or equivalent orchestration services.

Integrate AWS services with relational databases, APIs, file systems, and external applications.

Implement data ingestion from CSV, XML, JSON, Excel, fixed-length, variable-length, and delimited files.

Develop data validation, reconciliation, audit, retry, and exception-handling processes.

Optimize AWS Glue jobs for performance, scalability, and cost efficiency.

Implement secure access using AWS IAM roles, policies, encryption, and secrets management.

Support production deployments, incident resolution, root-cause analysis, and performance tuning.

Collaborate with DevOps teams to implement CI/CD pipelines for AWS Glue jobs and related infrastructure.

Prepare technical documentation, data flow diagrams, operational procedures, and support documentation.

Requirements

8+ years of experience in Python development and data engineering.

Strong hands-on experience with AWS Glue and PySpark.

Excellent knowledge of Python programming, object-oriented programming, and exception handling.

Experience designing ETL pipelines and data processing frameworks.

Strong experience with Amazon S3, including bucket structures, lifecycle policies, partitioning, and file formats.

Experience with Amazon EventBridge for scheduled and event-driven execution.

Experience developing and deploying AWS Lambda functions using Python.

Experience with Amazon SNS and SQS for notifications, messaging, and asynchronous processing.

Experience with Amazon CloudWatch for logging, monitoring, alerting, and troubleshooting.

Understanding of AWS IAM, security policies, encryption, and least-privilege access.

Experience working with relational databases such as Oracle, PostgreSQL, MySQL, or Amazon RDS.

Strong knowledge of SQL and database connectivity from Python or AWS Glue.

Experience working with REST/SOAP APIs and external system integrations.

Understanding of JSON, XML, CSV, Excel, and fixed-width file formats.

Experience with Git and software development best practices.

Preferred Skills

Experience with AWS Step Functions or AWS Glue Workflows.

Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab, or AWS CodePipeline.

Knowledge of data quality, reconciliation, lineage, and audit requirements.

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