• Lead, mentor, and develop a team of DevOps engineers, fostering a culture of excellence, collaboration, and continuous learning • Provide leadership-level coverage during US evenings and weekends to ensure rapid response to critical incidents and maintain platform stability • Drive strategic planning and coordination of DevOps initiatives during US business hours, working closely with engineering, product, and business stakeholders • Oversee architecture and implementation of scalable AWS and hybrid cloud infrastructure using Terraform/Terragrunt and related Infrastructure as Code tools • Guide the design, building, and optimization of highly available containerized environments leveraging EKS, Kubernetes, and Docker • Lead the automation strategy for CI/CD pipelines (TeamCity, GitHub Actions, ArgoCD, and similar), ensuring fast, secure, and reliable software delivery across environments • Champion security by design, implementing guardrails, identity/access controls, and compliance-driven automation across infrastructure layers • Collaborate with global teams in Poland to optimize handoffs, knowledge sharing, and round-the-clock operational coverage • Manage incident response processes, conduct post-mortems, and implement preventive measures to reduce future incidents • Establish and maintain monitoring, alerting, and observability practices using tools like Prometheus, Grafana, ELK/EFK, Datadog, or similar • Develop and track key performance metrics for infrastructure reliability, deployment velocity, and team productivity • Drive continuous improvement in deployment processes, system resilience, and cost optimization across multiple environments • Lead recruitment efforts to build and scale the DevOps team as business needs evolve

• Architect and lead the design of complex, enterprise-scale data pipelines using Airflow, DBT, and Databricks • Define and implement strategies for pipeline performance optimization to support real-time and batch processing at scale • Lead the design and optimization of AWS-based data infrastructure, including S3, Lambda, and Snowflake architecture • Establish and enforce best practices for cost-efficient, secure, and scalable data processing across the organization • Design and optimize AWS SageMaker environments for ML teams, ensuring optimal performance and resource utilization • Lead cross-functional collaboration with ML, Data Science, and Reporting teams to establish data strategy and ensure seamless data accessibility • Design and implement comprehensive data pipeline monitoring, alerting, and logging frameworks to proactively detect failures and performance bottlenecks • Architect automation solutions for data quality, lineage tracking, and schema evolution management • Lead incident response efforts, performing complex troubleshooting and root cause analysis for critical data issues • Champion and evolve Data DevOps best practices, driving automation, reproducibility, and scalability across the organization • Mentor junior and mid-level engineers, conducting code reviews and providing technical guidance • Establish technical standards, document complex infrastructure patterns, data workflows, and operational procedures • Evaluate and recommend new technologies and tools to improve data infrastructure and workflows.

• DevOps Software Development

• Ensure the reliability, scalability, and performance of production systems • Design resilient architectures • Define reliability standards • Improve observability and incident response • Reduce operational toil through automation • Contribute to codebases • Collaborate on system design • Help evolve engineering culture toward SRE best practices