Senior Data Engineer

About Voyc

Voyc is a fast-growing, remote-first startup, leading the way in AI-powered conversation intelligence and compliance monitoring software 

Our innovative technology enables businesses in highly regulated industries – think financial services, insurance providers, lenders, to monitor 100% of their customer call interactions—helping them to mitigate risks, improve compliance, and most importantly, provide an exceptional customer experience.

Voyc is no ordinary startup – we’re a young, remote-first company but we’re growing fast and we are already profitable!

The role

As a Senior Data Engineer, you will play a crucial role in ensuring that our data infrastructure is scalable, reliable, and future-proof. You will design and maintain high-performance data pipelines, manage Elasticsearch clusters, and ensure that our data flows efficiently across our AI-driven platform. You’ll work closely with engineering, product, and data science teams to create scalable, robust, and future-proof solutions. We are looking for someone who can connect the dots across features, systems, and business objectives—anticipating scalability challenges and ensuring our platform is always ahead of demand.

Key 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.

Required Skills & Experience 

• Proven experience in designing and implementing scalable data pipelines
• 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.
• Familiarity with Kafka, ksqldb or other stream processing frameworks.
• 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.

Nice to Have (Bonus Skills) 

• Experience in agile/scrum environments with data engineering teams.
• Experience with data lakes and querying large-scale datasets.
• Experience integrating machine learning models into data pipelines.
• Knowledge of cloud-based data engineering architectures

Tech Stack You’ll Work With 

• Data Pipelines: Kafka, ksqlDB, Python, Redis
• Storage & Analysis: Elasticsearch (cluster management and optimisation), AWS S3, PostgreSQL
• DevOps & Infrastructure: AWS

Benefits include stock options, generous vacation and training allowance.

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