Data Engineer: Build Scalable Pipelines & AI-Ready Data

Socket.dev; White House (TN); On-site; USD 90,000 - 130,000; Full time

Job summary

VantageWorks is seeking a Data Engineer to build and support the data infrastructure powering our growing organization. You'll develop data pipelines, improve data quality, and create scalable solutions for reporting, BI, and future AI initiatives.

Join an environment that values curiosity, independence, and collaboration, with opportunities to influence the data ecosystem and work directly with leadership.

Qualifications

• 1–3 years of relevant data engineering experience.
• Strong SQL skills for writing, debugging, and optimizing queries.
• Python (Pandas) for data work.
• Experience with cloud data platforms such as Fabric, Databricks, Snowflake, or Synapse.
• Experience building ETL/ELT pipelines.
• Experience integrating APIs and flat-file data.
• Strong analytical and problem-solving skills.
• Ability to work independently and collaboratively.

Responsibilities

• Design, build, and maintain scalable ETL/ELT data pipelines.
• Integrate data from APIs, flat files, cloud platforms, and systems.
• Clean, validate, transform, and document data.
• Write, optimize, and troubleshoot SQL queries.
• Develop Python scripts for automation and data transformation.
• Collaborate with business stakeholders.
• Support data quality and governance.
• Contribute to cloud-based data architecture.
• Partner with external consultants.
• Help establish the foundation for AI and advanced analytics.

Skills

SQL proficiency

Python data processing

Analytical thinking

Independent work

Communication

Tools

Microsoft Fabric

Databricks

Snowflake

Azure Synapse

Job description

VantageWorks is seeking a Data Engineer to build and support the data infrastructure powering our growing organization. You'll develop data pipelines, improve data quality, and create scalable solutions for reporting, BI, and future AI initiatives.

Join an environment that values curiosity, independence, and collaboration, with opportunities to influence the data ecosystem and work directly with leadership.