Urgent Opening For AWS data Engineer

Job Description

Position Summary:

AWS ecosystem

Experience:

Core Responsibilities

• Design and manage ingestion of raw network, telemetry, and log data to build scalable data models and storage layers in S3.
• Design, build, and maintain Data pipelines using AWS Glue and PySpark, ensuring reliable transformation of high-volume, heterogeneous data sources.
• Apply data-wrangling and transformation techniques to clean, standardize, and enrich datasets for downstream use.
• Architect and optimize DataLake solutions using S3, Athena, and Redshift for efficient querying and schema evolution.
• Conduct exploratory data analysis (EDA) to validate data quality and support analytics readiness.
• Collaborate with data scientists to ensure data is clean, queryable, and aligned to analytical and modeling needs.
• Implement monitoring and observability practices to maintain data lineage, integrity, and pipeline reliability.
• Continuously improve existing pipelines, ensuring scalability, cost-efficiency, and fault tolerance across the AWS ecosystem.

Tools & Ecosystem

AWS Glue, S3, Athena, Redshift, Lambda, Step Functions, EC2
Python, PySpark, SQL, ETL frameworksAirflow (or similar orchestration), Git, CI/CD pipelinesMonitoring and observability with CloudWatch, AWS Glue metrics, and custom dashboards Optional exposure to log-streaming or observability tools such as Cribl, Splunk, or ELK Stack is a plus.

Attributes & Mindset

You design pipelines as evolving systems — thinking beyond data movement to how the entire ecosystem scales, interacts, and recovers.
You write production-grade, maintainable code that scales gracefully as data volume and complexity grow. You’re curious about the data itself, not just the code — always seeking to understand the story behind the numbers.

New Vision is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees