Site Reliability Engineer Data Engineer

Job Title: Capacity Engineer with Data Engineer Location : 100% Remote Role Duration : Fulltime Teams Meeting Interview Job Description: Tools & Technique sData Engineering Stack : SQL, Python, Spark, Airflow for data processing and orchestration. - 3-4 years [we can go little lower also fine ]Monitoring & Observability : Prometheus, Grafana, Datadog .Chaos Engineering : Test system resilience under stress .Infrastructure as Code : Terraform, Ansible, Harness . Data Engine er with stron g Site Reliability Engineering (SR E) expertise i n capacity planni ng. This role ensures our infrastructure scales efficiently to meet user demand, balancing performance with cost. The engineer will forecast growth, analyze usage trends, and automate resource provisioning to prevent outages, over-provisioning, or under-provisioning. In addition, the role requires building robust data pipelines and analytical models to support forecasting and decision-makin g. Key Responsibilit ies Data Pipeline Developm ent: Design and maintain ETL/ELT pipelines to collect, transform, and store infrastructure usage d ata.Data Model ing: Build models to analyze system metrics and predict future resource ne eds.Demand Forecast ing: Analyze historical usage patterns to predict CPU, memory, and storage requireme nts.Load Testing & Scal ing: Simulate traffic spikes to identify bottlenecks and ensure systems scale linea rly.Cost Efficie ncy: Optimize resource allocation to avoid unnecessary costs while maintaining service availabil ity.Automat ion: Use Infrastructure as Code (IaC) tools like Terraform to automate scaling and provision ing.Architecture Rev iew: Collaborate with software teams to flag single points of failure and ensure resilient service des ign. Tools & Techn iques Monitoring & Observab ility: Prometheus, Grafana, Da tadog.Chaos Engine ering: Test system resilience under s tress.Infrastructure as Code: Terraform, Ansible, Ha rness.Data Engineering Stack: SQL, Python, Spark, Airflow for data processing and orchestr ation. Qualifi cations Strong backgr ound in data eng ineer ing and SRE p r actices.Hands-on experien ce with capacity planning, forecasting, and scaling.Profici ency in I aC tools (Terraform, Ansible, H arness).Experien ce with data pipelines, ETL/ELT frameworks, and big da t a tools.Familiari ty with monitoring/observability p latforms (Prometheus, Grafana, D atadog).Knowl edge of chaos eng ineering and resilience testing.Excellent collaboration and communication skills.