Data Engineer

Job Description

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.

Core Responsibilities (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 strategic mindset by envisioning future possibilities and successfully translating them into breakthrough data strategies, contributing to the organization's long-term success.
• Engaged: Not only shares our values but also possesses the essential competencies needed to thrive at Redica, as outlined here.