Big Data Developer
Columbus, NE - USA
Job Summary
About the Role
The Big Data Developer will play a critical role on the Big Data engineering team designing and implementing large-scale data processing systems that power scientific research and innovation. The ideal candidate has hands-on experience building enterprise-grade data pipelines working with distributed systems and optimizing data processing workflows.
This is a long-term project (12 months) with high visibility cutting-edge tools and opportunities to influence technical direction.
What Youll Do
Data Pipeline Design & Development
- Design build and deploy scalable data pipelines for ingesting processing transforming and storing high-volume datasets.
- Implement streaming and batch-processing solutions using Hadoop Spark and cloud-based tools.
Data Architecture & Engineering
- Develop and maintain data architecture and data flow models.
- Ensure data reliability accuracy and integrity across all environments.
- Support data warehousing strategies and best practices.
Data Quality Security & Compliance
- Implement automated data validation error handling and monitoring.
- Ensure compliance with internal security controls and regulatory standards.
- Partner with governance teams to enforce data quality and security guidelines.
Cross-Functional Collaboration
- Work closely with data scientists analysts product teams and application developers.
- Translate business requirements into robust technical solutions.
- Participate in Agile ceremonies and contribute to technical design discussions.
Performance Optimization
- Tune Spark applications Hadoop jobs and distributed data systems for performance and cost efficiency.
- Troubleshoot bottlenecks and implement improvements to system performance.
Technical Leadership
- Provide mentorship to junior developers and contribute to coding standards best practices and technical documentation.
Required Skills & Qualifications
- 4 years of Big Data Development experience in Hadoop ecosystems
- 2 years of hands-on development with Apache Spark
- Proficiency in Java Scala or Python
- Strong understanding of distributed systems ETL data warehousing and data modeling concepts
- Experience with large-scale datasets performance tuning and troubleshooting
- Strong problem-solving communication and collaboration skills
- Bachelors degree in Computer Science Engineering or related discipline
Preferred Skills
- Experience working with AWS cloud services (EMR S3 Lambda Glue etc.)
- Experience with Spark 3.x or 4.x
- Exposure to Kubernetes Airflow or similar orchestration tools
- Familiarity with CI/CD and DevOps automation for data engineering
Why This Opportunity Stands Out
- Long-term project stability (12 months likely extension)
- Ability to work on high-impact scientific and research-driven datasets
- Hands-on cloud modernization (AWS) and next-generation big data tooling
- Collaborative and innovative engineering culture