Python Data Engineer

GLINT TECH SOLUTIONS LLC
Plano, TX, United States
2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Airflow Amazon Web Services Amazon S3 Microsoft Azure Extract Transform Load (ETL) Data Warehousing Apache Hadoop Hadoop Distributed File System Python (Programming Language) PostgreSQL MongoDB MySQL
+9 more
NumPy Performance Tuning SQL Databases Workflow Management Systems Data Processing Apache Spark Pandas Pyspark Data Pipelines

Job description

Build and optimize scalable ETL/ELT pipelines Develop data models and workflows Ensure data quality, validation, and performance optimization Integrate data from multiple enterprise data sources

Requirements

Do you have experience in Workflow management (operations management method)?, Strong Python development experience (ETL, automation, data processing) Hands-on experience with Palantir Foundry/Gotham PySpark, Pandas, NumPy SQL (PostgreSQL/MySQL) and MongoDB Airflow or similar workflow orchestration tools AWS, Azure, or GCP experience Spark, Hadoop, S3, HDFS, and data warehousing concepts

About the company

Glint Tech Solutions is hiring a Python Data Engineer for our client, a leading telecommunications technology company. We are seeking a highly skilled professional with strong experience in Palantir Foundry/Gotham to support enterprise-scale data engineering initiatives.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on indeed.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:57 min

Core technical practices for robust data engineering

Sandhya Menon Sandhya Menon · WWC Europe 2026

2:34 min

Maximizing execution memory effectively via python numpy broadcasting

Jodie Burchell · LIVE

2:03 min

Accelerating pandas dataframes using cudf module plugins

Ankit Patel Ankit Patel · WWC 2024

2:18 min

Scaling MySQL databases for massive user growth

Johannes Nicolai Johannes Nicolai +1 · LIVE

3:33 min

Refactoring data science workflows using Rapids QDF and Pandas

Paul Graham Paul Graham · LIVE

1:25 min

Replacing NumPy with cuPy for straightforward GPU acceleration

Paul Graham Paul Graham · WWC 2025

Videos

See all

Related articles

See all