Senior Data Engineer

Summary

Join Voyc, a fast-growing, profitable, remote-first startup in AI-powered conversation intelligence and compliance monitoring software, as a Senior Data Engineer. You will play a crucial role in ensuring our data infrastructure is scalable, reliable, and future-proof. Design and maintain high-performance data pipelines, manage Elasticsearch clusters, and ensure efficient data flow across our AI-driven platform. Collaborate with engineering, product, and data science teams to create scalable solutions. Anticipate scalability challenges and ensure the platform stays ahead of demand. We offer stock options, generous vacation, and a training allowance.

Requirements

• Proven experience in designing and implementing scalable data pipelines
• Deep experience with managing and optimising Elasticsearch clusters, including performance tuning and scalability
• Strong proficiency in ETL processes and data transformation techniques
• A holistic understanding of how data systems interact within a broader platform, considering business goals and customer journeys
• Proficiency in Python, Scala, or Java for data processing and automation
• Knowledge of DevOps and automation practices in data engineering
• Strong analytical and problem-solving skills with attention to detail and data integrity
• Excellent communication and collaboration skills, with a proven ability to work with cross-functional teams

Responsibilities

• Architect, implement, and optimise data pipelines that support AI-driven analytics, reporting, and insights
• Take a big-picture view of data infrastructure, understanding how different systems interact within our platform and their impact on customer workflows
• Collaborate closely with cross-functional teams (engineering, product, and data science) to align data solutions with business and customer needs
• Design and maintain data models and schemas to optimise data storage and query performance
• Improve performance and scalability of data ingestion and processing, ensuring our platform can handle increasing data demands
• Drive best practices for data engineering, implementing standards for ETL, data governance, and pipeline monitoring
• Evaluate and integrate new technologies that enhance our data processing and analytics capabilities
• Mentor junior data engineers, fostering knowledge sharing and best practices across the team

Preferred Qualifications

• Experience in agile/scrum environments with data engineering teams
• Familiarity with Kafka, ksqlDB, or other stream processing frameworks
• Experience with data lakes and querying large-scale datasets
• Experience integrating machine learning models into data pipelines
• Knowledge of cloud-based data engineering architectures

Benefits

• Stock options
• Generous vacation
• Training allowance