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Lead performance testing for OCC’s clearing and settlement systems, designing failover and load tests to meet regulatory RTO/RPO targets using LoadRunner, JMeter, Gatling, Python, Java, and Kafka.
Lead enterprise-scale performance testing and automation for OCC’s critical clearing, risk, and settlement systems, designing rigorous, compliant test strategies for cloud-native, containerized, and event-driven architectures.
Build the control plane for enterprise AI agents: define APIs, policy engines, and observability to govern multi-cloud agent estates across AWS, Azure, Google, and third-party runtimes.
Build and maintain a Databricks-based BI platform, writing PySpark ETL pipelines and orchestrating workflows in Azure Data Factory to feed Power BI dashboards for a global security services company.
Build and maintain Databricks-based ETL pipelines and lakehouse architecture to power Securitas’ global BI platform, using PySpark, Delta Lake, and Azure Data Factory.
Build and maintain CI/CD pipelines, cloud infrastructure, and observability for secure identity and anti-fraud systems using AWS, GitLab CI, Terraform, and Kubernetes.
Designs and enforces data lifecycle policies on AWS and Azure, automating migrations and ensuring governance, compliance, and cost optimization.
Designs and owns production-ready AI and GenAI solutions, including LLMs, RAG, agentic systems, and MLOps/LLMOps pipelines, ensuring reliability, safety, and cost efficiency.
Own and secure EnerSys’s Azure and Kubernetes platform, ensuring reliability, observability, and safe AI workload operations while automating infrastructure and enforcing DevSecOps practices.
Senior Data Engineer builds and maintains cloud cost visibility pipelines using Python, SQL, dbt, Airflow, AWS Glue, Athena, Aurora, and Snowflake to power cost optimization insights.
Build and own the user experience for AI-powered healthcare tools, turning complex AI capabilities into intuitive, secure interfaces using React/Next.js and collaborating with ML teams.
Build and run a cloud-based data lakehouse platform for a fintech client, automating deployments, monitoring performance, and optimizing Kubernetes clusters with tools like Dremio, Spark, and Prometheus.
Design, build, and maintain secure, scalable cloud infrastructure on AWS/Azure/GCP using IaC (Terraform), CI/CD pipelines, and Kubernetes, while optimizing for cost, security, and reliability in a healthcare-focused environment.
Design, build, and automate secure cloud infrastructure on AWS/Azure/GCP using Terraform, Kubernetes, and CI/CD pipelines to support healthcare research workloads.
Design, build, and maintain secure, scalable cloud infrastructure on AWS/Azure/GCP using Terraform, Kubernetes, and CI/CD pipelines to support clinical research workloads.
Build and secure CI/CD pipelines, Kubernetes clusters, and FinOps tooling for a fintech platform that fights financial crime in real time.
Designs and maintains scalable cloud infrastructure on Google Cloud Platform (GCP), focusing on Kubernetes, Redis, CDN, and observability tools like Prometheus and Grafana.
Lead a team of data engineers to build and scale a modern Data Lakehouse (AWS S3, Iceberg, EMR) and transformation frameworks (dbt) for a global streaming platform, enabling self-serve analytics and AI readiness.
Design and automate cloud-native CI/CD pipelines and infrastructure as code for AWS/Azure/GCP, deploying microservices and ensuring observability, security, and cost optimization for enterprise customers.
Build and maintain automated guardrails for enterprise data platforms (Snowflake, Databricks, Cloudera) to ensure security, cost-efficiency, and scalability while enabling fast-moving engineering teams.
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