Job Description

We are the Product Development (PD) Platform Operations team, the driving force behind Ford's next-generation infrastructure and software solutions. Our mission is to build scalable, highly available environments that empower our engineers to design and build the vehicles of the future. We thrive on innovation, embracing cutting-edge technologies and methodologies like Infrastructure-as-Code, Configuration-as-Code (powered by Ansible), and cloud-native development - all while using CI/CD methodologies.

Qualifications:

Proven experience managing & operating Elastic Search clusters in a production environment, demonstrating a deep understanding of its architecture, performance tuning, and best practices Strong scripting or programming skills (e.g., Python, Bash, Go) for automating tasks, developing health checks, and integrating monitoring tools Experience with cloud platforms (e.g., AWS, Azure, GCP) and familiarity with cloud-native monitoring and logging services Experience working with a PLM platform, such as Siemen's Team Center and/or Dassault Systems 3DX Excellent problem-solving skills, a proactive mindset, and the ability to remain calm and effective under pressure Strong communication and collaboration skills, with the ability to work effectively across technical and non-technical teams

Requirements:

3+ years of experience In Data Engineering and analytics for DevOps, or similar role with a strong focus on monitoring, observability, and incident management 2+ years of hands-on experience managing & scaling Elastic Search in production environments. You must have prior experience with Elastic. Experience with other SRE tools / monitoring tools like Prometheus, Grafana, ELK stack, Dynatrace or similar Experience with IT applications with manufacturing - Good to have Experience working within an Agile/DevOps environment is a plus

Responsibilities

As a

Data Engineer (Elasticsearch Specialist)

, you will design, build, and optimize data pipelines that feed into Elasticsearch clusters, enabling high-performance search and analytics. You will be responsible for ingestion, transformation, indexing, and query optimization of large-scale data. This role requires a deep understanding of Elasticsearch architecture, data modeling, and performance tuning, along with strong data engineering and automation skills.

Key Responsibilities:

Data Ingestion & Pipelines

: Design and implement robust ETL/ELT pipelines to ingest structured, semi-structured, and unstructured data into Elasticsearch.

Elasticsearch:

Manage and optimize Elasticsearch clusters for scalability, availability, and performance. Configure index settings, mappings, analyzers, and sharding strategies to improve query efficiency.

Data Modeling & Indexing

: Develop efficient index designs to support various use cases (search, analytics, monitoring). Ensure proper use of aggregations, filters, and full-text search for optimal performance.

Proactive Monitoring

: design, implement, and manage comprehensive monitoring and alerting systems for our platforms, with a specific focus on Elastic clusters. This includes defining key metrics, thresholds, and escalation procedures to proactively identify and address potential issues

Health Check Management:

develop and maintain a suite of automated health checks for critical endpoints, APIs, infrastructure components, and network paths, ensuring rapid detection of anomalies & service degradations *

Collaboration

: work closely with development teams to ensure the reliability and scalability of applications that interact with Elastic, providing guidance on best practices and performance optimization