Data Engineer
Content + Source + Freshness • 11 Dec 2025 • 95% confidence
Offer value
High value score due to the demand for data engineering skills, reputable employer, and strong project involvement.
- Opportunity to work in a high-demand field with competitive skills
- Involvement with cutting-edge technologies like GCP
- Potential for significant professional growth in data engineering
- Requires strong technical knowledge with specific tools and technologies
Pros
- Involvement in key data engineering projects
- Opportunity to work with modern technologies like GCP and Airflow
- Strong potential for skill development in big data
Cons
- On-site requirement limits flexibility
- Competition for roles in a high-demand field
- W2 only contract may deter some candidates seeking other arrangements
Who it's for
Mid-Level • On-site
Good fit
- Experienced data engineers proficient in Python and data systems
- Candidates eager to work with big data and cloud technologies
- Professionals who enjoy solving complex data challenges
Not recommended for
- New graduates without relevant experience
- Individuals preferring fully remote opportunities
- Those averse to hands-on technical work
Motivation fit
Key skills
About the job
STRATEGIC STAFFING SOLUTIONS HAS AN OPENING!
Job Title: Data Engineer
Location: Charlotte, NC ** On-Site
Duration: 12 Months (Possible Extension)
Role Type: W2 Contract Engagement
Job Summary:
We are seeking a Data Engineer with strong experience in Python, PySpark, and Airflow, and hands-on knowledge of Cloudera Hadoop environments. You’ll be responsible for building and maintaining scalable data pipelines, enabling high-quality data flow and transformation across the organization. Infosec experience and Google Cloud Platform (GCP) familiarity are strong pluses.
Key Responsibilities:
- Design, build, and maintain robust, scalable, and efficient data pipelines using PySpark and Airflow.
- Manage and optimize large-scale data workflows on Cloudera Hadoop
- Develop reusable code in Python for data ingestion, transformation, and delivery.
- Ensure data quality, integrity, security, and performance across all pipelines.
- Work cross-functionally with data analysts, data scientists, InfoSec, and DevOps teams.
- Support data integration projects involving on-premise and cloud systems, particularly GCP.
- Participate in incident resolution, root cause analysis, and implement process improvements.
- Implement best practices for data security, governance, and access control, especially in regulated environments.
Required Qualifications:
- 3–6 years of professional experience in data engineering or related fields.
- Strong coding skills in Python and experience using PySpark for big data processing.
- Hands-on experience with Apache Airflow for orchestrating ETL workflows.
- Deep understanding of Cloudera Hadoop (HDFS, Hive, Impala, etc.).
- Solid understanding of data pipeline design, performance optimization, and data lake/data warehouse concepts.
Preferred Qualifications:
- Google Cloud Platform (GCP) experience, particularly with BigQuery, Dataflow, or Cloud Storage.
- Exposure to data security practices, InfoSec principles, or experience working in a regulated data environment.
- Familiarity with version control systems (e.g., Git) and CI/CD pipelines.
- Experience working in agile environments and using Jira/Confluence.
Soft Skills:
- Strong problem-solving and analytical thinking skills.
- Excellent communication skills—able to collaborate with technical and non-technical stakeholders.
- Detail-oriented, with a focus on performance, reliability, and maintainability.
The four pillars of our company are to:
- Set the bar high for what a company should do
- Create jobs
- Offer people an opportunity to succeed and change their station in life
- Improve the communities where we live and work through volunteering and charitable giving
