![]() Experience working with different data models and database schemas.Experience in ETL and data warehousing in on-premise and AWS environments.Experience designing and programming ETL/ELT for EDWs.Experience using various Hadoop technologies (HDFS, Hive, Spark, Unix shell scripting, HQL/SQL, Python or Scala, Oozie, Sqoop, TDCH).Experience automating predictive workflows leveraging open source & cloud-based platforms.Experienced designing and implementing large on-prem and cloud-based data warehouse solutions utilizing cluster and parallel RDMS and NoSQL architectures. ![]() Representative Cloud Data Architect resume experience can include: The work experience section should be the detailed summary of your latest 3 or 4 positions. It's meant to present you as a wholesome candidate by showcasing your relevant accomplishments and should be tailored specifically to the particular cloud data architect position you're applying to. This section, however, is not just a list of your previous cloud data architect responsibilities. It’s the one thing the recruiter really cares about and pays the most attention to. The section work experience is an essential part of your cloud data architect resume. Engineering support to update and maintain the data repository, data guidance documents, roadmaps, technical briefings, data access design and policies, and ODS backlog.Engineering support to provide updates and provide new processes, procedures, and guidance as data services are developed and refined.Engineering support for the requirements analysis and breakdown of capabilities from other programs and RFC for inclusion in ODS.Provide expertise to resolve critical, complex technical issues around Big Data and Analytic technology.Partner with Data Lake Architects to identify and resolve functional gaps in the Cloud Data architecture, and define new Cloud Architecture to meet emerging Data Lake needs.Maintain a strong collaborative relationship with the business owners and application owners in support of business strategies.Design, build and deliver the operational and management tools, frameworks and processes for the Data Lake and drive the implementations into the Data Lake Cloud Operations team. ![]()
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