Job Description
Join the Frontlines of Digital Democracy
As the 2026 Presidential Election approaches, the demand for robust, secure, and intelligent data infrastructure reaches a critical apex. We are seeking a visionary Senior Data Engineer to architect the backbone of our voter analytics, real-time reporting systems, and AI-driven predictive modeling platforms. This is not just a job; it is a mission to secure the integrity of democratic processes through cutting-edge technology.
In this high-stakes role, you will design scalable data pipelines capable of processing millions of records in real-time, ensuring data privacy compliance at the highest level, and integrating machine learning models to forecast voter sentiment. You will work directly with policy strategists and security experts to build a resilient digital ecosystem for the upcoming election cycle.
Responsibilities
- Architect Scalable Data Pipelines: Design and maintain high-throughput, fault-tolerant data pipelines using Apache Kafka and Spark to process real-time voter data and social sentiment analysis.
- AI & Machine Learning Integration: Collaborate with data scientists to deploy and optimize machine learning models that support predictive polling and demographic targeting.
- Infrastructure Security: Implement rigorous data governance and security protocols to protect sensitive voter information and prevent cyber threats.
- System Reliability: Ensure 99.99% uptime for reporting dashboards and internal communication tools during critical election periods.
- Data Warehousing: Lead the migration and management of large-scale data warehousing solutions (Snowflake/Redshift) to support long-term historical analysis.
- Team Leadership: Mentor junior engineers and conduct code reviews to maintain high engineering standards across the team.
Qualifications
- Experience: 8+ years of experience in software engineering, with at least 4 years specifically focused on data engineering and large-scale distributed systems.
- Tech Stack: Proficiency in Python, SQL, and experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes).
- Data Processing: Deep expertise in stream processing technologies (Kafka, Flink) and batch processing frameworks (Spark, Hadoop).
- Security Compliance: Strong understanding of data privacy laws (GDPR, CCPA) and government-grade security standards.
- Problem Solving: Demonstrated ability to troubleshoot complex system issues under pressure in a high-availability environment.
- Communication: Excellent written and verbal communication skills to translate technical requirements for non-technical stakeholders.