Steneral Consulting

Needs to Architect a solutions to transition and migrate their Hadoop & OLAP environment to BigQuery.. Strong knowledge of Google BigQuery, BigTabble, BQscript, Dataproc, Cloud composer (Airflow), Vertrx ML, Spark Scala platform.. In addition, the Data Solutions Architect will be critically engaged in our cloud transition, including the unification in a single environment of Hadoop and OLAP (Exadata) environments in our cloud environment, leveraging the metadata/data cataloging/data transformation lineage capabilities to support current and growing data governance processes, including a growing explicit privacy data architecture that will go beyond access and obfuscation, and extend to granular PHI segmentation.. Experience working with data management strategy development especially in regards uses of metadata, data lineage, data security, privacy and data life cycle management.. Knowledgeable of Google Bigquery platform, Bigtable, BQscript, Dataproc, Cloud composer (Airflow), Vertrx ML, Spark Scala platform.

data solutions architect

Positions: Data Solutions Architect Location: Arlington, VA ( Hybrid ) Duration: 6 mcth Process: 2 steps, via Video interviews, background check, start US Citizen or GC only Keys/Notes <ul><li>Industry leader in digital prescriptions and transactions.</li><li>Over 5 million transactions daily and over 14 billion annually</li><li>Needs to Architect a solutions to transition and migrate their Hadoop & OLAP environment to BigQuery. </li><li>Min of 3 years in a Data Solutions Architect role or leadership role. </li><li>Strong knowledge of Google BigQuery, BigTabble, BQscript, Dataproc, Cloud composer (Airflow), Vertrx ML, Spark Scala platform.</li><li>Data lake experience</li><li>Python</li><li>Automation </li></ul>As a Data Solution Architect, you will strategically define, develop, and maintain target architectures while translating business needs into data and system requirements. This role is responsible for managing information-centric architecture views to visualize data domains and interactions across the organization, with a focus on eliminating redundancy and minimizing complexity in system designs. The Data Solutions Architect will contribute to the development of the target state architecture by considering stakeholder concerns, business capability requirements, data governance, security, privacy, and data management principles. They will collaborate with other architects, data engineers, and business analysts in evolving metadata stores, CI/CD processes, and larger scale data representation structures. In addition, the Data Solutions Architect will be critically engaged in our cloud transition, including the unification in a single environment of Hadoop and OLAP (Exadata) environments in our cloud environment, leveraging the metadata/data cataloging/data transformation lineage capabilities to support current and growing data governance processes, including a growing explicit privacy data architecture that will go beyond access and obfuscation, and extend to granular PHI segmentation. Responsibilities <ul><li>Translate business needs into data and system requirements and manage information-centric architecture views to quickly visualize data domains and data interactions across the organization, by eliminating/minimizing data and process redundancy in system designs, reducing complexity of data extraction and exchange among systems.</li><li>Evolve the target state architecture based on stakeholder concerns, business capability requirements, scope, constraints, data governance, security, privacy, and data management principles.</li><li>Participate in early technology demonstrations of core or adjacent technologies to further the desired architecturally significant changes.</li><li>Facilitate an architectural roadmap and influence prioritized backlog that contains key technologies, design standards, frameworks, and guidelines needed to realize that evolving target state architecture.</li><li>Given the dynamic nature of our environment, this role is also in part an engineering position in that the incumbent will participate in hands-on early proof-of-concept demonstration work. Aid in early phase preliminary project scoping, feasibility efforts, technology/data solutions, integration, and automation.</li><li>Facilitating the integration of metadata requirements into the central metadata repository as part of software delivery lifecycle cross enterprise.</li><li>Creation and maintenance of architecture artifacts e-g conceptual data model, current and future state system model, integration, and access model etc.</li><li>Day to day collaboration with Data Engineers, BI Engineers, Analytics Engineers, and Product Owners from the Data & Analytics organization, Business and Product Analysts from our Product Innovation organization, and Software Engineering teams.</li><li>Strategic collaboration with Enterprise architecture and engineering, Data Governance, the Privacy Office, and AI and machine learning teams. </li></ul>Qualifications Basic Requirements: <ul><li>Bachelor’s Degree in the field of computer science, information systems, or computer engineering and 8+ years of equivalent work experience.</li><li>8+ years of experience in a combination of enterprise information or data architecture, and data engineering with at least 3 years in a technical leadership capacity.</li><li>Experience working with data management strategy development especially in regards uses of metadata, data lineage, data security, privacy and data life cycle management.</li><li>Significant understanding of enterprise information management disciplines and practices.</li><li>Basic background in OLAP but with strong knowledge of big data such as Hadoop stack and cloud platforms experience.</li><li>Demonstrated ability to work programmatically in such environments, including but not limited to, automation frameworks utilizing python and jvm based languages.</li><li>Knowledgeable of Google Bigquery platform, Bigtable, BQscript, Dataproc, Cloud composer (Airflow), Vertrx ML, Spark Scala platform.</li><li>Strong knowledge of various Business Intelligence architecture, data warehouse, data marts, data lake, lakehouse, semantic layer and reporting layers.</li><li>Research and data analysis skills.</li><li>Creative thinking and problem-solving abilities.</li><li>Great communication and collaboration skills to work with various levels of enterprise partners.</li></ul>

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