Data and Analytics Architect

3 weeks ago

New York, United States Verinext Full time

Join Verinext, a technology company that's not just keeping up with the future, but actively shaping it. At Verinext, we firmly believe that work should be as enjoyable as it is rewarding. As a Data and Analytics Architect, you'll be stepping into an environment that thrives on innovation and fun. Our team-oriented culture isn't just a buzzword; its a cornerstone of our success. Were incredibly proud to have been recognized as a "Best Place to Work" by the Philadelphia Business Journal for 10 consecutive years.

Position Purpose We are seeking a Data and Analytics Architect to join our dynamic team. The ideal candidate will be responsible for designing and leading the implementation of modern data platform solutions that enable organizations to manage and prepare data for analytics and AI use cases. The modern data platform is an integrated ecosystem of technology that supports traditional batch ETL, real-time data streaming, data transformation, and workload-specific storage. The candidate must also have strong knowledge of analytics tools that support visualization (dashboards / reports) and self-service analytics. This role involves deep technical acumen and strong communication skills, as it bridges the gap between our clients' needs and our technical implementation teams.

Job Responsibilities Assess current state of customer data and analytics platforms across their enterprise and recommend architecture, technology and process updates for improved ability to leverage data to achieve business outcomes Assist customers in making informed decisions regarding data and analytics architecture and technology selection. Drive consensus on business and technical data strategy decisions and ensure that appropriate resources are employed to deliver high quality results. Design and implement modern solutions for data processing, storage and analysis, including real-time streaming, batch ETL, data lake, data warehouse, lakehouse, mesh, etc. Design and oversee implementation of analytics systems including BI dashboards, self-service analytics and predictive / prescriptive analytics Author and maintain current data architecture and governance documentation with traceability to concrete data products Define executive-level KPI’s, create management and operational reports, and deliver well-informed and repeatable business intelligence solutions Design and oversee implementation of data models supporting customer requirements Perform R&D, acquire, and consume data from external partner and vendor systems as part of overall customer solution Understand and own legacy data problems, identify constraints that block client(s) from supporting large scale solutions in terms of storage volume and throughput capacity. Ensure all build vs. buy data decisions and vendor solutions are continuously evaluated for fit against client(s) business strategy, considering rapid technology change and switching costs

Qualifications Expert in data architecture methods and tools, strategic planning, business intelligence systems, data storage models, real time data stores, enterprise integration patterns, and KPI frameworks for large and complex solutions Strong knowledge of leading data platforms such as Azure Data Fabric, Apache Spark, Kafka, Databricks, etc. Some experience with data science and willingness to learn/grow with client(s) needs to build advanced analytics solutions Experience in enterprise-class problem solving and data architecture definition impacting $10M’s to $100M’s in strategic outcomes. Ability to leverage the right level of data architecture processes to provide tangible strategic value on an ongoing basis Ability to think big and dive deep; to personally touch the data and technologies for validating strategic recommendations Experience with implementing, tuning, and scaling large data stores with 100M’s of records to optimize performance and cost Hands-on experience to create and manage Data platform while setting best practices for security, privacy, monitoring, alerting, and CI/CD Knowledge of emerging DataOps methods and tools B.S. in Computer Science, Data Science or related field (M.S. preferred)

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