Posted:1 day ago|
Platform:
Work from Office
Full Time
Key Responsibilities:
* Design, develop, and maintain **ETL pipelines** using **AWS Glue, PySpark, and Python**.
* Migrate large-scale datasets from **Amazon S3** or **SQL Server** to **PostgreSQL (RDS/On-Prem/Cloud)**.
* Optimize data extraction, transformation, and loading for performance and cost efficiency.
* Implement **data validation, reconciliation, and error handling mechanisms** to ensure accuracy.
* Work with **AWS services** including Glue, S3, Lambda, Step Functions, CloudWatch, and IAM.
* Collaborate with **DBA, Data Engineering, and Analytics teams** to define requirements and optimize schemas.
* Monitor, troubleshoot, and resolve ETL job failures or performance bottlenecks.
* Ensure compliance with **security, governance, and best practices** in data handling.
* Strong hands-on experience with **AWS Glue, PySpark, and Python**.
* Expertise in **PostgreSQL** and **SQL Server** (schema design, indexing, query optimization).
* Experience in migrating data from **structured/unstructured sources (S3, RDS, on-prem SQL Server)**.
* Solid understanding of **data warehouse concepts, ETL best practices, and data governance**.
* Familiarity with **AWS ecosystem (Athena, Redshift, Kinesis, Step Functions, CloudFormation)** is a plus.
* Strong problem-solving, debugging, and performance-tuning skills.
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