Data Engineer 9
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Key skills for this role
Role Overview
Support, develop, and maintain a data and analytics platform.
Process, store, and make data available to analysts and other consumers.
Work with Business and IT teams to enable agile data delivery at scale.
Key Skills for This Role
Full Job Posting
Job Summary
Support, develop, and maintain a data and analytics platform.
Process, store, and make data available to analysts and other consumers.
Work with Business and IT teams to enable agile data delivery at scale.
Core Data Engineering Responsibilities
- Automate distributed systems for ingesting and transforming relational, event-based, and unstructured data.
- Monitor and troubleshoot data quality and data integrity issues.
- Implement data governance processes for metadata, access, and data retention.
- Develop scalable data pipelines with monitoring and alert mechanisms.
- Develop physical data models and data storage architectures.
- Analyze data flows, dependencies, and relationships for conceptual, logical, and physical data models.
- Test and troubleshoot data pipelines and operate distributed cloud-based data platforms.
Enterprise Data Products
- Develop and maintain data pipelines, transformations, and curated datasets supporting reporting, analytics, automation, and GenAI use cases.
- Create reusable, discoverable, and governed data assets with metadata, lineage, and quality controls.
- Collaborate with product managers, data engineers, data scientists, and solution engineers on AI-ready data products.
Required Qualifications
- Experience with data integration, ETL or ELT processes, data pipelines, and data transformations using modern cloud-based technologies.
- Working knowledge of data modeling, SQL, data quality, metadata management, and data governance.
- Ability to translate business and product requirements into scalable, performant, maintainable, and reusable solutions.
- Experience working in Agile, cross-functional teams.
- Bachelor's degree in a relevant technical discipline or equivalent practical experience.
Technology Experience
- Preferred technologies include Big Data open source tools, Spark, Scala or Java, MapReduce, Hive, HBase, Kafka, and SQL.
- Preferred experience includes clustered cloud computing, large-file movement, analytical solutions, and IoT technology.
- Preferred exposure includes Data-as-a-Product models, data catalogs, lineage, AI-ready datasets, and GenAI initiatives.
Competencies
Translate stakeholder needs into verifiable requirements and maintain requirements traceability.
Collaborate effectively, communicate clearly, focus on customers, and make timely decisions.
Write and test code, scripts, and build automation using version control and quality practices.
Document solutions, validate changes, measure quality, and solve systemic data problems.
Role Information
- The source describes the role category as on-site with flexibility and states that it is not 100% on-site.
- The source identifies the job type as exempt and experienced.
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