Job Title: Senior Data Engineer
Location: Los Angeles, CA, 90012
Duration: 12 Months
Skills Required:
• Cloud Platforms: Deep understanding of Azure ecosystem, including Azure Data Factory, Data Lake Storage, Blob Storage, power apps, and Functions. Additionally, in-depth understanding and implementation of API management such as Apigee.
• Big Data Technologies: Proficiency in Databricks, Spark, PySpark, Scala, and SQL.
• Data Engineering Fundamentals: Expertise in ETL/ELT processes, data pipelines, data modeling, schema design, and data warehousing.
• Programming Languages: Strong Python and SQL skills, with knowledge of other languages like Scala or R beneficial.
• Data Warehousing and Business Intelligence: Strong ERD concepts, designs, and patterns, Understanding of OLAP/OLTP systems, performance tuning, Database Server concepts, and BI tools (Power BI, Tableau).
• Data Governance: Strong understanding of RBAC/ABAC, Data Lineage, Data leak prevention, Data security, and compliance. Deep understanding and implementation knowledge of audit and monitoring in Cloud.
• Infrastructure Deployment: GitHub version control, CI/CD pipelines, release management, Terraform and YAML templates, and script-based deployments.
Work Experience Required:
• Seven (7) years of applying Enterprise Architecture principles, with at least five (5) years in a lead capacity.
• Five (5) years of hands-on experience with Azure Data Factory, Azure Databricks, API implementation and management solution, and managing Azure resources.
• Five (5) years of experience in the following: developing data models and pipelines using Python; working with Lakehouse platforms; GitHub CI/CD pipelines and infrastructure automation, Terraform scripting; and with data warehousing systems, OLAP/OLTP systems, and integration of BI tools.
Education/Training Required:
• This classification requires possession of a bachelor's degree in an IT-related or Engineering field.
#TB_EN
#ZR
