Senior Data Engineer

We are looking for an experienced Senior Data Engineer to serve as a Hands-On Tech Lead & Individual Contributor. In this role, you will spend roughly 70% of your time in the code, designing, building, and optimizing our core data platform, and 30% mentoring and guiding junior-to-mid-level engineers. You will set technical standards, lead code reviews, break down complex architectural requirements into actionable tasks for junior team members, and ensure the team delivers scalable, high-quality data pipelines. Core Responsibilities  Technical Leadership & Mentorship (Lead IC) Guide & Mentor: Serve as the technical point of contact for junior and mid-level data engineers, conducting thorough code reviews, pair programming, and guiding them on best engineering practices. Architectural Oversight : Drive technical decisions across data sub-systems, translating high-level product requirements into clean, scalable, and maintainable engineering tasks for the team. Agile Execution : Work closely with Engineering Managers and Product Managers to prioritize technical backlog items, estimate effort, and break down complex epics into digestible work items for junior developers. Hands-On Engineering & Execution (IC) Data Pipeline Development: Design, build, and maintain scalable ETL/ELT data pipelines, APIs, and microservices for high-volume regulatory and health agency datasets. Data Reliability & Integrity: Identify root causes of data quality issues and implement automated testing, monitoring, and validation frameworks to ensure data accuracy. System Integration & ML: Integrate data processing pipelines with downstream NLP/ML services and search engines (ELK stack). Production Operations: Ensure reliable system deployments to production and assist operations teams in resolving complex escalated pipeline or database incidents. About you Tech Savvy : Effectively anticipates and adopts innovations in business-building technology solutions, staying up-to-date with data advancements and incorporating them into work processes Manages Complexity : Actively synthesizes solutions from complex information by identifying patterns and developing effective problem-solving strategies to solve data-related problems effectively Decision Quality : Consistently makes good and timely decisions that propel organizational progress and maintain data integrity Collaborates : Actively engages in collaborative problem-solving by leveraging diverse perspectives and finding innovative solutions to achieve shared goals and data engineering initiatives Optimizes Work Processes : Actively seeks opportunities to enhance and streamline current work processes for managing data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing Drives Results : Strives to continuously improve performance and exceed expectations to contribute to overall success and meet data-related deliverables Strategic Mindset : Consistently demonstrates a…