Oteemo Inc.
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Technical Talent Acquisition | Employee Engagement | People Operations | Human Resources
As a Senior Data Engineer, you will be part of our team that provides data architecture and infrastructure support to our customers. You will be responsible for assessing current architectures and designing future-state architectures for on-premise and cloud based implementations. These systems and platforms can span various infrastructure components from operating systems and hypervisors, COTS products, custom applications and Big Data platforms. You will work alongside a highly skilled infrastructure automation team to ensure your designs are implemented at the highest levels of fidelity. You will also work with development teams to ensure their code is optimized and compatible with the latest software versions. You will be rapidly gathering requirements and configurations to accomplish the project objectives. This role is essential for ensuring system reliability, enabling rapid incident detection, and empowering data-driven decisions. Responsibilities: Design and implement scalable data ingestion pipelines for both batch and real-time data from diverse structured and unstructured sources Perform extensive data profiling, transformation and enrichment to prepare clean, ML ready datasets for data scientists and analysts Develop custom reports and data visualizations to support analytics, decision-making across business and technical teams Collaborate with data scientists and business teams to deliver curated datasets and reporting needs for ML and observability analytics Qualifications: 7+ years of experience in data engineering, with a focus on building scalable data pipelines and observability frameworks Proven track record building ETL/ELT pipelines for structured, semi-structured, and unstructured data Expertise in designing and optimizing dashboards, visualizations, and custom analytics solutions using Kibana, Splunk, Grafana, or BI tools Ability to translate complex observability and platform metrics into business insights for leadership and product teams Proven experience with Splunk (search processing language, dashboards, alerting) for large-scale log management and analysis Strong expertise in Dynatrace for application performance monitoring (APM), tracing, and end-to-end visibility Proficiency with Elastic Stack (Elasticsearch, Logstash, Kibana, Beats) for log aggregation, storage, and querying Strong knowledge of distributed systems, microservices, and cloud-native environments (AWS, Azure, or GCP) Experience in automation and scripting (Python, Bash, PowerShell, or similar) to streamline monitoring processes Familiarity with container orchestration platforms (Kubernetes, Docker) and CI/CD pipelines Knowledge of ITIL/ITSM practices, incident management, and RCA methodologies Strong ability to collaborate with stakeholders across data science, analytics, platform engineering, and product teams to design data solutions Experience with security information and event management (SIEM) solutions Understanding of infrastructure-as-code (IaC) tools such as Terraform or Ansible Knowledge of service level objectives (SLOs), SLIs, and error budgets Familiarity with other monitoring tools like Prometheus, Grafana, Loki, or OpenTelemetry Employment details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Information Technology Industries: IT Services and IT Consulting Referrals increase your chances of interviewing at Oteemo Inc. by 2x
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As a Senior Data Engineer, you will be part of our team that provides data architecture and infrastructure support to our customers. You will be responsible for assessing current architectures and designing future-state architectures for on-premise and cloud based implementations. These systems and platforms can span various infrastructure components from operating systems and hypervisors, COTS products, custom applications and Big Data platforms. You will work alongside a highly skilled infrastructure automation team to ensure your designs are implemented at the highest levels of fidelity. You will also work with development teams to ensure their code is optimized and compatible with the latest software versions. You will be rapidly gathering requirements and configurations to accomplish the project objectives. This role is essential for ensuring system reliability, enabling rapid incident detection, and empowering data-driven decisions. Responsibilities: Design and implement scalable data ingestion pipelines for both batch and real-time data from diverse structured and unstructured sources Perform extensive data profiling, transformation and enrichment to prepare clean, ML ready datasets for data scientists and analysts Develop custom reports and data visualizations to support analytics, decision-making across business and technical teams Collaborate with data scientists and business teams to deliver curated datasets and reporting needs for ML and observability analytics Qualifications: 7+ years of experience in data engineering, with a focus on building scalable data pipelines and observability frameworks Proven track record building ETL/ELT pipelines for structured, semi-structured, and unstructured data Expertise in designing and optimizing dashboards, visualizations, and custom analytics solutions using Kibana, Splunk, Grafana, or BI tools Ability to translate complex observability and platform metrics into business insights for leadership and product teams Proven experience with Splunk (search processing language, dashboards, alerting) for large-scale log management and analysis Strong expertise in Dynatrace for application performance monitoring (APM), tracing, and end-to-end visibility Proficiency with Elastic Stack (Elasticsearch, Logstash, Kibana, Beats) for log aggregation, storage, and querying Strong knowledge of distributed systems, microservices, and cloud-native environments (AWS, Azure, or GCP) Experience in automation and scripting (Python, Bash, PowerShell, or similar) to streamline monitoring processes Familiarity with container orchestration platforms (Kubernetes, Docker) and CI/CD pipelines Knowledge of ITIL/ITSM practices, incident management, and RCA methodologies Strong ability to collaborate with stakeholders across data science, analytics, platform engineering, and product teams to design data solutions Experience with security information and event management (SIEM) solutions Understanding of infrastructure-as-code (IaC) tools such as Terraform or Ansible Knowledge of service level objectives (SLOs), SLIs, and error budgets Familiarity with other monitoring tools like Prometheus, Grafana, Loki, or OpenTelemetry Employment details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Information Technology Industries: IT Services and IT Consulting Referrals increase your chances of interviewing at Oteemo Inc. by 2x
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