Sr. Data Platform Engineer

Cyara is the global leader in AI-powered customer experience assurance, committed to eradicating bad CX. As the only unified platform for continuous testing and monitoring across voice, digital, messaging, and conversational AI channels, Cyara empowers hundreds of the world’s leading brands to optimize more than 350 million customer journeys every year. With enterprises rapidly deploying agentic AI systems that adapt, learn, and make autonomous decisions in real time, Cyara provides the assurance layer that turns pilots into production-ready deployments—testing AI agents with AI agents to catch what scripts can’t. From full journey visibility to AI governance, trust validation, and compliance, Cyara ensures every touchpoint works flawlessly and every AI interaction solves customer problems while delighting them in the process. Cyara helps businesses deliver secure, friction-free, and high-quality CX at scale. Interested to find out more about us?  Check out:  www.cyara.com Cyara’s Values:  At Cyara, our values shape everything we do. We're passionate about Delivering Excellence by putting the customer first, collaborating globally, and always striving to improve. We take smart risks and Innovate Boldly, setting new standards and learning from every experience. Integrity First is our cornerstone—we value humility, authenticity, and respect for diversity, building trust in all we do. We Embrace Curiosity by empowering you to experiment, learn, and grow in a dynamic environment. At Cyara, our values drive us forward, shaping a culture where innovation and excellence thrive.  Cyara’s Diversity, Equity, Inclusive and Belonging:  At Cyara, we are dedicated to fostering a workplace that embodies equal opportunity and champions diversity, equity, inclusion, and belonging (DEIB). We strive to cultivate an environment where every individual feels valued, respected, and empowered to bring their whole selves to work, contributing unique perspectives and talents. Our commitment includes continuously evaluating and enhancing our policies, practices, and culture to align with our DEIB principles. We ensure a discrimination-free environment where individuals are evaluated solely on their merits and abilities, regardless of legally protected statuses such as sex, race, color, ethnicity, national origin, age, religion, disability, sexual orientation, gender identity, veteran status, or medical condition. By celebrating our differences and championing inclusivity, we enrich our organization, make more thoughtful decisions, and drive collective success.  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:

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:

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.