Senior/Principal Data Engineer
Position Overview
A leading technology organization is seeking a Senior or Principal Engineer to lead the development of a next-generation data infrastructure initiative focused on identity intelligence. This greenfield project will serve as the backbone for a suite of advanced fraud prevention and identity verification solutions.
The ideal candidate will bring deep expertise in data architecture, graph databases, and backend engineering, along with a passion for building scalable systems that power real-time analytics and machine learning. This role offers high visibility and strategic impact, with direct support from senior leadership.
Key Responsibilities
- Architect and implement scalable, secure, and high-performance data platforms using modern cloud technologies.
- Lead and mentor a team of engineers through design reviews, code reviews, and technical guidance.
- Define and enforce best practices in data engineering, including testing, deployment, and data governance.
- Design solutions using data lakes, warehouses, and graph databases to model complex relationships.
- Build and maintain ETL pipelines for batch and streaming data to support both model training and inference.
- Develop low-latency APIs for querying graph data and generating machine learning features.
- Collaborate with legal and security teams to ensure compliance with data privacy and regulatory standards.
- Communicate technical concepts clearly to both technical and non-technical stakeholders.
- Stay current with emerging technologies in big data, graph analytics, and cloud infrastructure.
- Contribute to open-source initiatives and engage with technical communities.
Ideal Qualifications
- 10-15+ years of experience in data engineering, with at least 4 years in a leadership role.
- Proven track record of building and scaling data systems in AWS, GCP, or Azure.
- Proficiency in Python, SQL, and one or more of Java, Scala, or Go.
- Hands-on experience with streaming frameworks (e.g., Spark, Kafka, Flink).
- Deep knowledge of graph databases (e.g., Neo4j, Neptune, OrientDB) and graph algorithms.
- Strong foundation in software architecture, design patterns, and data structures.
- Experience with Docker, Kubernetes, and microservices architecture.
- Familiarity with CI/CD pipelines and DevOps practices.
Preferred Skills
- Experience building ML feature pipelines using platforms like Databricks.
- Knowledge of cybersecurity, compliance, and identity resolution.
- Expertise in GraphQL APIs, JVM performance tuning, and caching strategies.
- Background in fraud detection systems or similar high-impact domains.
FAQs
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