Databricks Data Engineer

CSS Staffing; Moncks Corner (SC); Hybrid; USD 117,000 - 143,000; Full time

Benefits offered by this job

Comprehensive medical, dental, andvis

Retirement program

Paid time off

Tuition reimbursement and professional

Tuition reimbursement and professional

Job summary

CSS Staffing is seeking a Senior Data Engineer for a hybrid role across South Carolina or North Carolina. You will design scalable ETL/ELT pipelines with Databricks, build Lakehouse solutions, and support AI and analytics initiatives.

You’ll collaborate with data scientists and analytics teams, implement streaming and batch processing, and ensure data quality, governance, and performance across the enterprise.

Qualifications

• 7+ years of enterprise data engineering experience.
• 2+ years of hands-on Databricks experience building and supporting production data pipelines.
• Advanced SQL and Python programming skills.
• Experience cloud-native data solutions in Azure or GCP; AWS also considered.
• Experience developing both streaming and batch processing solutions.
• Strong understanding of dimensional modeling and Lakehouse architecture.

Responsibilities

• Design, develop, and optimize scalable ETL/ELT pipelines using Databricks and cloud tech.
• Build and support Lakehouse solutions with Medallion Architecture, Delta Lake, and Star Schema.
• Develop both streaming and batch data pipelines for analytics.
• Engineer reliable data assets for reporting, analytics, AI, and ML initiatives.
• Partner with data scientists and analytics teams to prepare production-ready datasets and support ML models and API integrations.
• Improve data quality, governance, monitoring, and platform performance.
• Collaborate with business stakeholders, analysts, architects, and software engineers.
• Communicate technical concepts effectively to both technical and non-technical audiences.
• Represent the data organization in cross-functional meetings and initiatives.

Skills

SQL

Python

Cloud data platforms

Streaming & batch processing

Data modeling

ETL/ELT design

Stakeholder communication

Tools

Databricks

Informatica

Azure Data Factory

Delta Lake

Spark

Job description

Senior Data Engineer Full-Time | Contract-to-Hire or Direct Hire South Carolina or North Carolina (Hybrid).

We are seeking an experienced Senior Data Engineer to join a growing enterprise data organization that is investing heavily in cloud technologies, modern data architecture, AI, and advanced analytics. This is an opportunity to design and build enterprise data solutions that support analytics, machine learning, and operational decision-making across a large organization.

Responsibilities

• Design, develop, and optimize scalable ETL/ELT pipelines using Databricks and modern cloud technologies.
• Build and support Lakehouse solutions utilizing Medallion Architecture, Delta Lake, and dimensional modeling techniques including Star Schema.
• Develop both streaming and batch data pipelines supporting enterprise analytics.
• Engineer reliable data assets that enable reporting, advanced analytics, AI, and machine learning initiatives.
• Partner with data scientists and analytics teams to prepare production-ready datasets and support ML models and API integrations.
• Improve data quality, governance, monitoring, and overall platform performance.
• Collaborate with business stakeholders, analysts, architects, and software engineering teams across the enterprise.
• Communicate technical concepts effectively with both technical and non-technical audiences.
• Represent the data organization professionally in cross-functional meetings and enterprise initiatives.

Required Qualifications

• 7+ years of enterprise data engineering experience.
• 2+ years of hands‑on Databricks experience building and supporting production data pipelines.
• Strong experience with enterprise ETL platforms such as Informatica, Azure Data Factory, or comparable enterprise integration technologies.
• Advanced SQL and Python programming skills.
• Experience developing cloud‑native data solutions in Azure or Google Cloud Platform preferred; AWS experience will also be considered.
• Experience developing both streaming and batch processing solutions.
• Strong understanding of dimensional modeling, Star Schema, data warehousing, and modern Lakehouse architecture.
• Excellent written and verbal English communication skills.
• Comfortable presenting technical solutions to business stakeholders and leadership.
• Ability to confidently communicate with business leaders and represent the Data Engineering team in cross‑functional and enterprise‑wide meetings.

Preferred Qualifications

• Experience supporting AI and machine learning initiatives.
• Experience integrating enterprise applications through REST APIs.
• Experience with Apache Spark, Delta Lake, and Databricks notebooks.
• Experience implementing data governance, metadata management, and data quality frameworks.
• Experience working within large enterprise data environments.

Compensation & Benefits

• $130,000 base salary once FTE
• Comprehensive medical, dental, and vision benefits
• Retirement program
• Paid time off
• Tuition reimbursement and professional development support
• Opportunity to work on modern cloud, AI, and enterprise analytics initiatives