Data Engineer III
Indexed description
About The Role
This role performs moderate-complexity research, design, and data engineering assignments within a defined engineering functional area or product line, with emphasis on Python development basics, workflow automation, AI-enabled process improvement, and production support readiness.
Responsibilities
- Own and manage assigned data transfers, including collection setup, transfer setup, contributor onboarding, and customer onboarding activities.
- Partner with technical stakeholders to gather, analyze, document, and finalize business and technical requirements for data engineering solutions.
- Design, develop, maintain, and support efficient, reusable, and high-quality Python-based data pipelines, workflows, and automation solutions.
- Write and review technical specifications, oversee dataflow and database structures, and ensure compliance with engineering standards and best practices.
- Troubleshoot production and data engineering issues, perform root cause analysis, implement bug fixes, and drive permanent corrective actions.
- Monitor pipeline health, data quality, SLA adherence, and operational performance while providing L2/L3 production support, incident management, and service recovery.
- Collaborate with cross-functional teams to translate product requirements into scalable data engineering solutions and continuously improve processes through automation and AI-driven approaches.
- Participate in code reviews, project reviews, operational documentation, knowledge development, and ongoing learning to deliver high-quality services aligned with changing business priorities.
- 4+ years of experience in Data Engineering or Data Management with demonstrated technical competency and experience supporting production data pipelines and systems.
- Bachelor’s degree in Engineering, Computer Science, or a related field, or equivalent practical experience.
- Strong proficiency in Python for data processing, scripting, pipeline development, automation, operational tooling, and production support activities.
- Proficiency in SQL and data manipulation/query languages, with solid understanding of file management and data transfer processes.
- Experience with automation frameworks and tools to improve reliability, operational efficiency, scalability, and service quality.
- Working knowledge of AI-assisted techniques, software engineering best practices, Agile methodologies, and development environments including Windows, Unix, and HPCC.
- Strong analytical, problem-solving, communication, collaboration, and attention-to-detail skills, with the ability to learn new tools, technologies, and processes.
- Hands-on experience in production support, including monitoring, alert triage, log analysis, incident management, stakeholder communication, service recovery, and operational documentation.
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