A company that's reimagining how attorneys and clients work together is looking for a Senior Data Engineer to join its growing Data Engineering team.
At this company, reliable and scalable data infrastructure isn't just a technical goal - it's at the heart of its ability to empower AI-driven innovation and enhance its product offerings. Understanding deeply the needs of its products and engineering teams, identifying the optimal data sources, architecting intuitive data models, and building robust data systems form the core of the company's mission.This is a high-impact role focused on designing, building, and scaling the company's Production Data Layer Infrastructure, the foundational systems that empower engineering teams to build data-driven features and that directly power the company's AI solutions. You will take ownership of developing and evolving core infrastructure used by product and backend engineers across the company. Your work will enable seamless access to high-quality, reliable data for both operational and AI-powered product use cases.Responsibilities:
- Lead the development and implementation of scalable, production-grade data infrastructure
- Partner closely with backend and platform teams to enable data-powered product development
- Build and maintain the data systems that serve both real-time and batch workloads for analytical and product needs
- Create robust, high-quality data pipelines and tooling with strong SLAs and high resilience
- Drive standards in data modeling, observability, orchestration, and governance
- Contribute to architectural decisions that impact the company's AI strategy and long-term scalability
- Mentor engineers and collaborate across R&D teams to elevate the technical capabilities of the team
Requirements
- 5+ years of experience as a Data Engineer, particularly within product engineering environments
- Hands-on Experience building data streaming infrastructure (e.g., Kafka, Flink), or workflow engines
- Strong expertise in PostgreSQL, Snowflake, and ClickHouse or other modern databases
- Advanced proficiency in SQL and Python
- Proven experience building and maintaining production-ready data systems that support both business intelligence and product logic
- Solid understanding of data architecture, and best practices for data reliability and scalability
- Bachelor’s or Master’s degree in Computer Science, Information Systems, or equivalent experience
- Strong communication and collaboration skills; comfortable working cross-functionally with engineering and product
Bonus Points
- Familiarity with Data Mesh architecture or decentralized data ownership models
- Experience with orchestration tools (e.g., Airflow) and distributed systems
- Experience building platforms that support AI/ML pipelines