Senior Data Engineer at Red Hat designing and optimizing 데이터 솔루션 supporting sales and forecasting. Collaborating with teams and applying modern data engineering practices to ensure data quality.
About the role
- Principal HR Data Engineer specializing in Microsoft Azure and Databricks Lakehouse platforms. Responsible for designing, implementing, and maintaining scalable data pipelines and architectures for analytics.
Responsibilities
- Design, develop, and maintain scalable, high-performance data pipelines and architectures leveraging Microsoft Azure and Databricks Lakehouse to enable data analytics and machine learning capabilities.
- Partner with data scientists, data analysts, business teams, and other stakeholders to understand data requirements and ensure high-quality data solutions are delivered in alignment with business needs.
- Implement and optimize ETL (Extract, Transform, Load) processes for the ingestion, transformation, and loading of data from diverse data sources into the Databricks Lakehouse environment.
- Optimize the performance and cost-efficiency of data storage solutions and data retrieval methods within the cloud ecosystem.
- Ensure data integrity, consistency, and security across all data pipelines, storage layers, and access points.
- Monitor data pipelines and associated infrastructure, troubleshooting and resolving any performance, data flow, or reliability issues.
- Stay current with emerging trends and best practices in cloud computing, big data technologies, and data engineering methodologies to drive continuous improvement.
Requirements
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field
- Relevant certifications—such as Microsoft Certified: Azure Data Engineer or Databricks Certified Data Engineer—are a plus.
- 7 or more years of experience as a Data Engineer with a focus on Microsoft Azure and Databricks Lakehouse technologies.
- Demonstrated experience working with HR or People data is strongly preferred, particularly within enterprise HCM, workforce analytics, or employee lifecycle reporting environments.
- Experience in designing, developing, and optimizing scalable data solutions in cloud environments.
- Working knowledge of machine learning and AI data pipelines, including how data engineering supports feature engineering, model training, and scalable analytics.
- Strong background in SQL, Python, PySpark, and other relevant programming languages.
- Extensive experience in ETL processes, data integration, and data warehousing.
- Data Management: Expertise in data modeling, data quality assurance, and applying industry-standard data governance practices.
- Cloud & Big Data Technologies: Familiarity with tools and frameworks like Azure Synapse, Azure Databricks, Apache Kafka, and Azure Data Factory.
- Problem Solving: Strong analytical and troubleshooting skills with an attention to detail.
- Collaboration: Excellent communication and collaboration skills to work effectively with cross-functional teams.
- Independence & Time Management: Ability to work autonomously, manage multiple projects, and prioritize tasks efficiently.
Benefits
- We prioritize your growth, development, and well-being to help you reach your full potential.
- Opportunities that fit your lifestyle and ambitions—whether you’re looking for part-time flexibility or full-time career advancement.
- Reasonable accommodations for applicants with disabilities.
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