Sr Data Engineer

Job highlights

• Engaged : Not only shares our values but also possesses the essential competencies needed to thrive at Redica,as outlined here Qualifications . 5+ years of senior or lead developer experience with an emphasis on technical mentorship,code / system architecture,and quality output
• Extensive experience designing and building data pipelines,data APIs,and ETL / ELT processes. .

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.

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 strategic mindset by envisioning future possibilities and successfully translating them into breakthrough data strategies, contributing to the organizations long-term success

• Engaged: Not only shares our values but also possesses the essential competencies needed to thrive at Redica, as outlined here Qualifications

  • 5+ years of senior or lead developer experience with an emphasis on technical mentorship, code/system architecture, and quality output
  • Extensive experience designing and building data pipelines, data APIs, and ETL/ELT processes
  • Deep, hands-on experience in Python
  • Hands-on experience setting up, configuring, and maintaining SQL and no-SQL databases (MySQL/MariaDB, PostgreSQL, MongoDB)
  • Computer Science, Computer Engineering, or similar technical degree

  Bonus Points

  • Experience with the data engineering stack within AWS is a major plus (S3, Lake Formation, Lambda, Fargate, Kinesis Data Streams/Data Firehose, DynamoDB, Neptune DB)

  • Experience with event-driven data architectures

  • Experience with the ELK stack is a major plus (Elasticsearch, Logstash, Kibana)

    Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.