What are the responsibilities and job description for the Data Engineer position at Randstad Digital | Torc?
Location: Raleigh, NC (onsite, 3 days/week)
Data Engineer
We're looking for a Data Engineer to develop and enhance application components that support ML/AI models and data ingestion pipelines. You'll lead and collaborate with a team of developers, work closely with business stakeholders, and ensure that data systems and statistical models are production-ready, resilient, and scalable.
How to apply
One application opens the door to every Raleigh engineering role we have open right now. Build your Torc profile once, and you’re findable for this role and every other req we’re working in the corridor.
What You'll Do
Data Engineering & Pipeline Development
- Design, develop, and maintain ETL pipelines and data ingestion processes supporting ML/AI models
- Build and enhance Hive and DBMS-based applications for large-scale data processing
- Develop PySpark and Spark jobs for big data transformation and analytics workloads
- Write and optimize Oracle SQL/PLSQL stored procedures and queries on Exadata
ML/AI Model Support
- Develop components that prepare and serve data for machine learning model training and inference
- Implement and deploy statistical models using Python libraries (scikit-learn, scipy, numpy, pandas)
- Work in Jupyter notebooks to prototype, evaluate, and document model pipelines
- Ensure models are production-ready with a focus on code resiliency and stability
Collaboration & Leadership
- Lead and mentor a team of developers on data engineering best practices
- Partner with business stakeholders to translate requirements into scalable data solutions
- Participate in design and code peer reviews
- Contribute to analysis of operational issues and drive resolution
- Work in a fast-paced Agile environment with minimal supervision
What We're Looking For (Required
- Strong knowledge of Oracle, SQL, and RDBMS systems including Oracle Exadata
- Hands-on experience with Hadoop, Hive, Spark, and PySpark for big data workloads
- Python programming proficiency including scripting and object-oriented design
- Experience with ETL development and data pipeline architecture
- Familiarity with statistical modeling libraries: Jupyter, scipy, numpy, pandas, scikit-learn
- Working knowledge of machine learning concepts and model lifecycle
Nice to Have
- Experience automating and deploying ML models in a production environment
- Knowledge of Autosys for job scheduling
- Prior experience with Horizon tools: Jira, Bitbucket
- Familiarity with Natural Language Processing (NLP) techniques including semantic search, classification, and information extraction
- Demonstrated ability to manage senior stakeholder expectations and build trust