Data Engineer

Virtuous Tech Inc.
Houston, United States
7 days ago
Apply on www.dice.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Business Analytics Applications Microsoft Azure Cloud Computing Continuous Integration Information Engineering Extract Transform Load (ETL) Data Warehousing DevOps Python (Programming Language) Standard Sql Google Cloud
+8 more
Azure Data Factory Apache Spark Data Lakes Pyspark AWS Glue Data Management Data Pipelines Databricks

Requirements

We are looking for an experienced Data Engineer with 8+ years of experience in building scalable data pipelines, data platforms, and analytics solutions., * 8+ years of experience in Data Engineering

  • Strong SQL and Python skills
  • ETL/ELT development
  • Data pipeline development and optimization
  • Experience with Databricks, Spark, or PySpark
  • Cloud experience with AWS, Azure, or Google Cloud Platform
  • Experience with data warehouses and data lakes
  • Azure Data Factory, AWS Glue, or similar tools
  • Strong understanding of data modeling
  • Experience with CI/CD and DevOps practices
  • Excellent analytical and problem-solving skills

Apply for this position

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

Apply on www.dice.com
Prepare application

Good distractions

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

55 sec

Validating data processing architectures via containerized events

Modood Alvi · World Congress 2025

4:32 min

Harnessing Spark with Python using PySpark and Py4J

Ayon Roy · LIVE

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · World Congress 2026 Europe

2:57 min

Core technical practices for robust data engineering

Sandhya Menon Sandhya Menon · World Congress 2026 Europe

3:37 min

Scaling machine learning pipelines from prototypes to petabytes

Julian Joseph · LIVE

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

Videos

See all

Related articles

See all