Senior Data Engineer | Onsite - Contract at TalentBurst, Inc.
Los Angeles, CA
About the Job
Job Title: Senior Data Engineer | Onsite
Location: Los Angeles, CA
Duration: 6+ Months
W2 Preferred (No Sponsorship Required)
Skills Preferred:
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.
Experience Required:
Miscellaneous/ Niche/ Other
Experience Preferred:
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 Required:
Miscellaneous/ Niche/ Other
Education Preferred:
This classification requires the possession of a bachelor's degree in an IT-related or Engineering field.
#TB_EN
Location: Los Angeles, CA
Duration: 6+ Months
W2 Preferred (No Sponsorship Required)
Skills Preferred:
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.
Experience Required:
Miscellaneous/ Niche/ Other
Experience Preferred:
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 Required:
Miscellaneous/ Niche/ Other
Education Preferred:
This classification requires the possession of a bachelor's degree in an IT-related or Engineering field.
#TB_EN