Job Description:

We are seeking a skilled Data Engineer - Production Support to join our data engineering and operations team. In this role, he/she will be responsible for the ongoing support, monitoring, troubleshooting, and optimization of data pipelines, databases, and related infrastructure. He/she will play a critical role in ensuring the availability, reliability, and performance of production data systems and processes. He/she directly supports data integration efforts (within the data marts, ad-hoc queries, and data services) by providing services that ensure Chubb is aligning IT efforts with business information needs. The ideal candidate will have 5+ years of experience working on data-driven projects, with hands on experience in ETL/ELT development, performance monitoring and enhancement, data analysis, and data quality assurance.

Key Responsibilities:

Monitor and support production data pipelines, ETL/ELT jobs, and batch processes.Troubleshoot data issues, perform root cause analysis, and implement long-term fixes.Collaborate with data engineers, analysts, and DevOps teams to ensure reliable data delivery.Optimize and maintain performance of SQL queries, stored procedures, and data workflows.Develop scripts and automation tools to improve support processes and reduce manual effort.Maintain detailed documentation of production incidents, fixes, and best practices.Participate in on-call rotations and respond to production outages as needed.Ensure data quality and integrity across multiple environments.Work with cloud platforms (e.g., AWS, Azure, GCP) and orchestration tools (e.g., Autosys, Airflow, dbt).
 

Qualifications:

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.5 years of experience in data engineering, data operations, or production support roles.Proficiency in SQL and data manipulation across large datasets.Experience with ETL/ELT tools and pipeline orchestration (e.g., Apache Airflow, Informatica, Talend).Familiarity with cloud technologies such as Azure, AWS, or Google Cloud PlatformFamiliarity with scheduling tools such as AutosysStrong troubleshooting and analytical skills.Experience with scripting languages such as Python, Bash, or PowerShell.Experience in CI/CD pipelines for data infrastructure.Exposure to data governance and security best practices.Familiarity with version control (Git) and agile development methodologies.Knowledge of data modeling and warehouse architecture.Strong communication and collaboration skills.Ability to work under pressure and manage multiple tasks.High attention to detail and commitment to data quality.