Quotum Technologies Inc.
Description (Remote Until Covid-19) The Data Warehouse Architect will drive the adoption of cloud data services across the enterprise ensuring emerging business goals are met while maintaining a consistent and stable DW landscape. Cloud DW Architect will be responsible for delivering high quality solutions for applications using heterogeneous data sources. With hands-on experience leveraging Cloud Services focused on RDBMS technologies ndash you will be responsible for designing, building, migrating, maintaining robust Data Lake Data Analytics solutions. Act as an SME for migrating on-prem applications to cloud-based PaaS services primarily focusing on DW and Big Data solutions, using modern technology stack. Provide guidance in building multi-terabyte DW strategy. Architect Scalable Data Analytics solutions, including technical feasibility for Big Data Storage, Processing, and Consumption. Implement enterprise Data Lake heterogeneous data management methods. Must be able to research, present, articulate pros and cons of modern data tier technologies. Develop data-gathering methods for analyzing and synthesizing data. Work with Data Analysts, DBAs, and Business Stake Holders to define secure and performance optimized data rendering methods and self-service BI. Assist application teams in designing cloud data solutions incorporating security principles and best practices to ensure designs are in accordance with data security, governance, and costs. Designing Data Pipelines to support machine-learning solutions. Data science experience using Python, R statistical modeling, data mining, and operationalizing end-to-end cloud data analytics solutions is a plus. Thorough understanding of one or more IntegrationAnalysisReporting tools like Data Prep, SSIS, SSAS, Azure Data Factory, Pentaho, Segment etc. and proficient in migrating legacy ETL processes to cloud based solutions. Design, implementation, andor support of complex application architectures (i.e. having an architectural sense for connecting data sources, data visualization, structured and unstructured data) Build robust Web Analytics platform to track and analyze site visits, conversions, promo tracking, hit maps etc. Experience with tools like Google Analytics, Heap, Matomo etc. Requirements 10+ years of hands-on experience in Database engineeringBusiness Intelligence technologies. Proficient with Google Cloud Platform Analytics tool set such as Big Query, Looker, Dataproc, Dataflow, Cloud Data Fusion, Dataprep, also Azure Data factory, Data Bricks and Synapse Analytics etc. Hands on experience working with Analytics tools like Looker, Google Data Studio, Power BI, Tableau, Big Query, Sisense, Alteryx etc. Knowledge of Master Data Management (MDM) and Data Quality tools. Experience with Segment. Experience with Dev Ops and Cloud Solutions to implement (GitVSTSAutomated Deployment). Deep understanding in both traditional modern Data Architecture and Processing concepts, including various RDBMS systems (MS SQL, MySQL, Oracle, Maria DB), Big Data (Hadoop, Spark), Business Analytics Knowledge handling APIs as Data Sources using any language (Python, .NET, Azure Functions, Java) Open to relocate, commute, or local to Atlanta, Phoenix, SFO or NY. Certifications a Plus Azure and or Google Cloud Platform Data DW Engineer