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Our talented workforce of over 1500 employees provides a wide array of specialty services including construction, engineering, underground facility locating, fulfillment, and program management.
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Understanding of database internals, large-scale data processing, and data warehouse design. Database Query Engine (QA), Automation Infrastructure and Quality Engineering (AIQ), Cloud Platform & Deployment Engineering, Developer Productivity Engineering (DPE.
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Experience implementing and maintaining data platform core services (data lake, data integration, data warehouse) and configuring and integrating infrastructure and PAAS (e.g., Azure Data factory, Informatica cloud services, Databricks, Data gateway and Qlik Sense, Power BI.
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Basic knowledge of Lean/TPS core tools/processes and experience in core engineering and data analysis functions. - Knowledge of Warehouse Management operations, Industrial Engineering, and Lean methods.
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5+ years of experience working in technically complex environments, data warehouse, building REST APIs, microservices architecture, automated enterprise CI/CD tools and processes. We build and manage innovative internal and customer-facing solutions such as CnSight a lightweight and first of its kind modern and complex data warehouse-type microservice application designed to revolutionize how organizations manage their cybersecurity and through automated performance reporting.
ExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Partner with Engineering to optimize data tracking/quality and drive data warehouse improvements. Excellent SQL and data warehouse skills. Expertise with data visualization and dashboard tools such as Tableau, Looker, or equivalent.
ExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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A proven ability to work closely with data engineering partners to build scalable solutionsA passion for digging in, finding insights, and plugging gaps in an empowered way. A deep understanding of modern data architectures and technologies, including experience with SQL and Python, experience with dimensional data warehouse design, experience working with data from marketing, CRM and event tracking systems, experience using cloud data platforms, and experience with ETL and ELT tools.
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You have at least 10 years of deep architecture and engineering experience with expertise in: relational and NoSQL databases, data warehouse, big data/data lake, master data management, data modelling, data quality and governance, data engineering, BI reporting and analytics, data science, ML/AI, Python, Spark, AWS, and Azure.
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Snowflake started with a clear vision: develop a cloud data platform that is effective, affordable, and accessible to all data users. Snowflake developed an innovative new product with a built-for-the-cloud architecture that combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a fraction of the cost of traditional solutions.
InternExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Tooling and infrastructure automation for engineering productivity. Required Coursework: Algorithms, Data Structures, Operating Systems, Knowledge of data structures and algorithms.
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Exp designing and delivering data engineering solutions with Databricks Exp in Azure Databricks Experience in Data Engineer in zure Big Data Environment Expertise in ETL tools i.e. (Infomatica, Talend, SSIS, Data Stage) Expertise in Implementing Data Warehousing Solutions Exp with working in Agile (KANBAN, Scrumban) environment Exp in zure stack ( zure Data Lake, zure Data Factory) Exp in Scala or Python, T-SQL.
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Strong in data structure, ETL, data warehouse, and related data engineering technologies. 6+ years of experience in software engineering, and 2+ years in data engineering.
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The Data Warehouse Manager will also recruit and manage a strong engineering team, set direction, set goals, plan for their career growth, and provide mentorship for the team. The Data Warehouse Manager will be responsible and take ownership in supporting the EIA data and analytics portfolio that includes but is not limited to, resources that manage back-end data curation, data visualization, business data strategy, data governance, and other data warehousing and data science needs in the future to support the needs of EIA. This role will also work closely with other UCSF IT teams.
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The Data Engineering development team Is responsible for design, development, test and deployment of large enterprise data warehouse/BI data solutions using both on-prem and cloud technologies.
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Experience modeling data in a warehouse such as Snowflake, Redshift, and or BigQuery. Manage and provide leadership around data infrastructure and data engineering by overseeing development, customization, and management of data integration tools, databases, warehouses, and analytical systems.
ExpandApply NowActive JobUpdated 9 days ago
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