Sr. Data Platform Engineer

As the global leader in AI-powered customer experience assurance, we help some of the world's most recognized brands deliver seamless, reliable, and engaging interactions across voice, digital, messaging, and AI-powered channels. Every year, our platform helps optimize hundreds of millions of customer journeys, ensuring businesses can confidently deliver exceptional experiences at scale.

As enterprises race to deploy agentic AI, the defining question is no longer whether AI can handle customer interactions, it’s whether those interactions can be trusted. Cyara is the confidence layer that answers that question, testing AI agents with AI agents to detect hallucinations, validate decisions, and ensure compliance before failures ever reach your customers.

Joining Cyara means helping shape the future of customer experience, partnering with some of the world’s biggest brands, and working alongside passionate, talented people who are committed to making every customer interaction better.

The Data Platform Engineer is responsible for ensuring the reliability, availability, and cost efficiency of the Airbyte-based data ingestion platform running on Kubernetes. This role focuses on operating and monitoring production data sync infrastructure, ensuring data is reliably synced from source databases into downstream data pipelines, and maintaining strong observability and cost controls across AWS resources.

You will be responsible for

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Key Responsibilities

• End-to-End Data Migration: Architect and execute large-scale data migrations from legacy source databases to cloud targets using AWS DMS, Azure migration tools, or Airbyte.
• Kubernetes Orchestration: Own and operate the Airbyte infrastructure and data pipelines running on Kubernetes, ensuring seamless production handling and rapid incident resolution.
• Advanced Python Engineering: Design and build robust Python-based frameworks for automated monitoring, alerting, and high-performance ETL/ELT processing.
• Platform Reliability (SRE): Ensure high availability (99.9%+) of data ingestion workflows by performing root cause analysis (RCA) and implementing self-healing infrastructure.
• Cost & Performance Optimization: Manage and optimize cloud infrastructure costs (AWS/Azure) related to data sync workloads through precise resource tagging and performance tuning.
• Cloud Infrastructure & Security: Configure and maintain AWS resources (S3, IAM, EKS), ensuring strict adherence to the principle of least privilege and data security standards.

Let’s talk about your skills/expertise

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• Required Skills & Expertise

• Experience: 5–8 years of professional experience in Data or Platform Engineering roles.
• Migration Tools: Expert-level knowledge of AWS DMS, Azure Data Migration, or similar enterprise-grade replication tools.
• Coding Mastery: Strong Python skills for building custom ingestion utilities, monitoring agents, and automation scripts.
• Data Engineering Core: Deep understanding of Data Lakehouse architectures, dimensional modelling, and SCD Type 2 implementation.
• Kubernetes Proficiency: Hands-on experience with Docker/K8s (EKS/AKS), including pod health, rollouts, and service connectivity.
• Cloud Services: Solid experience with AWS (S3, IAM, CloudWatch) or Azure equivalent services.
• Observability: Familiarity with logging and metrics systems (Prometheus, Grafana, or ELK) to maintain platform health.

Cultural & Operational Fit

• Rapid Adaptability: Ability to quickly learn and adapt to new production environments, transitioning from design to deployment at a "production-ready" pace.
• Collaborative Mindset: Act as a bridge between infrastructure and downstream data consumers to resolve complex ingestion bottlenecks.
• Clean Code Advocate: Committed to Git-based workflows, CI/CD best practices, and structured documentation.