Data Engineer - Cloud & Analytics Pipelines

Jobvous Staffing Solutions, LLC
Houston, TX, United States
12 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Airflow Amazon S3 Data Analysis Microsoft Azure Cloud Computing Data Architecture Information Engineering Data Infrastructure Database Queries Python (Programming Language) Machine Learning
+12 more
Systems Development Life Cycle Azure Data Lake Software Engineering Feature Store Azure Data Factory Apache Spark Build Management Data Lakes AWS Glue Data Management Data Pipelines Databricks

Job description

Data Engineer - Cloud & Analytics Pipelines

Every AI system runs on clean data. Houston energy companies are building the pipelines that power their AI. They need you.

About the opportunity:

Jobvous Staffing Solutions is placing Data Engineers across Houston’s energy, financial services, and technology companies. As AI adoption accelerates across every industry, the demand for engineers who can build reliable, scalable data pipelines has never been higher.

If you build the plumbing that makes AI actually work - the pipelines, lakehouse architecture, and data infrastructure - we have multiple opportunities for you in Houston right now.

Responsibilities:

Design and build scalable data pipelines using Databricks, Spark, and Airflow

Implement Medallion / Lakehouse architecture on Azure Data Lake or AWS S3

Build feature stores and data infrastructure to support ML model training

Optimize pipeline performance, reliability, and cost at scale

Collaborate with data scientists and ML engineers to productionize models

Requirements

Software Engineering, Cloud Computing, Artificial Intelligence (AI), Data Management, Financial Services, Scalable System Development, Plumbing, Data Lake, Amazon Simple Storage Service (S3), Microsoft Windows Azure, 3+ years of data engineering experience with production pipelines

Strong Python and SQL proficiency

Databricks and Apache Spark experience required

Azure Data Lake, Azure Data Factory, or AWS Glue experience

Airflow or similar orchestration experience

Medallion / Lakehouse architecture experience is a strong differentiator

Energy sector domain experience is a plus - not required

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