Overview
Skills
Job Details
Job Title: Problem Manager (with DBT, Python, and Google Cloud Platform Expertise) US Onshore
Job Location: El Segundo, CA
Working Model: 4 days/week onsite.
Experience : 12-15 Years
Role Overview:
The Problem Manager is responsible for driving the identification, analysis, and resolution of recurring or high-impact issues within data engineering and analytics environments. This role focuses on continuous service improvement by leveraging advanced data transformation and analysis tools, particularly Data Build Tool (DBT), Python, and Google Cloud Platform (Google Cloud Platform), to ensure robust, scalable, and efficient data operations.
Key Responsibilities:
- Problem Identification & Analysis:
- Gather and analyze incident and operational data to identify root causes of recurring issues, trends, and potential failures within data pipelines and cloud environments.
- Use statistical and data analysis tools to interpret structured and unstructured data relevant to problem management.
- Technical Leadership:
- Design and orchestrate data transformation workflows using DBT on Google Cloud Platform, including modular SQL and Python-based models for BigQuery.
- Develop and maintain Python scripts for complex data transformations within the DBT framework, leveraging BigQuery DataFrames and cloud-native servicesEnsure secure deployment and execution of DBT jobs in containerized/cloud environments, applying best practices for access control and environment management.
- Coordination & Collaboration:
- Collaborate with incident management, change management, and data engineering teams to implement permanent fixes and prevent recurrence.
- Facilitate cross-functional teams in root cause analysis and resolution strategies, ensuring alignment with business priorities and technical requirements.
- Documentation & Knowledge Management:
- Maintain a comprehensive knowledge base of known errors, root causes, and workarounds for use by support and engineering teams.
- Document processes, solutions, and lessons learned to drive organizational learning and continuous improvement
- Stakeholder Communication:
- Communicate status, impact, and resolution plans to stakeholders at all levels, ensuring transparency and alignment
Required Skills and Experience:
- Technical Skills:
- Advanced proficiency in DBT for building, scheduling, and managing data transformation workflows, including experience with DBT Cloud or Core.
- Strong hands-on experience with Python for data engineering, automation, and analytics within cloud data environments
- Deep understanding of Google Cloud Platform services, especially BigQuery, IAM, and containerized job orchestration (e.g., Cloud Run)
- Familiarity with CI/CD practices, infrastructure-as-code (e.g., Terraform), and modern data architecture.
- Experience with incident and problem management tools, root cause analysis methodologies, and ITIL frameworks.
- Analytical & Management Skills:
- Excellent analytical thinking, pattern recognition, and troubleshooting skills.
- .
- Proven ability to coordinate technical teams and manage complex problem queues.
- Strong documentation, reporting, and communication abilities.
Preferred Qualifications:
- Bachelor s or Master s degree in Computer Science, Data Engineering, Information Systems, or related field.
- Experience in managing large-scale data platforms and ensuring high system availability.
- Knowledge of data security best practices, especially in cloud environments.
- Experience with other data transformation or orchestration tools (e.g., Airflow) is a plus.
Summary of Essential Tools:
Tool/Platform | Purpose in Role |
DBT (Data Build Tool) | Data transformation, workflow orchestration |
Python | Complex data manipulation, automation |
Google Cloud Platform (BigQuery, Cloud Run) | Scalable data storage, processing, and job orchestration |
ITSM/Incident Mgmt Tools | Problem/incident tracking, root cause analysis |
Knowledge Base/CMDB | Documentation and dependency management |
This role is ideal for a technically skilled problem solver who thrives in data-driven environments and can bridge the gap between engineering, operations, and business stakeholders using modern cloud and analytics technologies.