Data Engineer

JOB DETAIL

Job Title

Data Engineer

Job Location

Houston, TX (Onsite)

Job Duration

6+ Months Contract

Employment Type

W-2 Only

Mandatory Skills

Amazon S3 Buckets, Databricks, DevOps

Job Summary

We are seeking a skilled Data Engineer to support transactional database engineering, SQL Server assessment, PostgreSQL/Aurora migration, and database modernization initiatives. The ideal candidate will have strong SQL and data modeling expertise, along with experience in modern data platforms, cloud technologies, and DevOps practices.

Key Responsibilities

• Assess SQL Server environments and identify database modernization opportunities.
• Support migration from SQL Server to PostgreSQL/Amazon Aurora.
• Design and implement efficient data models and database architectures.
• Work with Databricks and Amazon S3 to support data engineering and analytics solutions.
• Implement lakehouse or medallion architecture patterns and develop analytical data products.
• Apply CI/CD, Terraform, and database DevOps practices to automate deployments.
• Implement automated schema validation and controlled database release processes.
• Support API-based data access, event-driven integrations, and data contracts.
• Help separate transactional, integration, and analytical data workloads.
• Ensure data quality, reliability, scalability, and compliance with organizational standards.

Required Skills and Qualifications

• 5–9 years of relevant data engineering experience.
• Strong experience with Amazon S3, Databricks, and DevOps.
• Experience in transactional database engineering and SQL Server assessment.
• Knowledge of PostgreSQL and Amazon Aurora migration.
• Strong understanding of data modeling and database modernization.
• Familiarity with lakehouse architecture, medallion patterns, and data catalogs.
• Experience with CI/CD, Terraform, database DevOps, and automated schema validation.
• Knowledge of domain-oriented architecture, APIs, event-driven integration, and data contracts.
• Experience in energy, trading, retail, financial services, or other data-intensive regulated industries is preferred.