Senior Cloud Data Architect

Leidos is seeking a seeking a customer experience focused Data Architect to work with a team of subject matter experts and developers to design and implement data architectures supporting end to end data processing needs. As a data architect, you will interface with functional professionals and business managers to translate business concepts and needs into cloud-based data architectures that support high-performance data and geospatial visualization and advanced analytics. You will be hands-on in establishing and overseeing implementation of data standards, data ingest, integration, storage, and query architectures. You will design solutions for data migration from/to a range of data architectures that include Microsoft SQL Server, cloud-based data stores such as Azure data lake, Azure SQL, Azure Analytics Services, Azure Synapse.

Responsibilities: • Work with client and Leidos functional team members and business managers to analyze and translate business needs into long-term data architectures. • Define conceptual, logical, and physical data models supporting high performance analytical queries in multiple subject areas. • Design and implement data architectures for relational, data lake, delta lake, medallion architecture, NoSQL data stores. • Design and deliver solutions using Microsoft Azure cloud services, including Azure data lake, Azure SQL, Azure Analysis Services, Azure Synapse. • Design and implement data models for OLAP cubes, star schema, subject specific data marts. • Design and implement processes, functions, and tools for data migration and conversion or refactoring of data models to support new architecture (e.g., SSAS cubes to AAS tabular models) • Provide guidance on data pipeline design and implementation. • Assist in the definition and maintenance of data modeling and data architecture design standards, tools, best practices. • Assist with the implementation of data management and data governance best practices and tools, including capabilities such as enterprise data catalog, data quality. • Suggest ideas to improve system performance and achieve cost efficiencies. • Experience establishing common business definitions, conformed dimensions, reusable measures, reference data, and data-modeling patterns that promote consistency and reuse across enterprise domains and reporting products. • Hands-on experience designing reusable SQL-based metrics and detail layers in SQL Managed Instance or comparable relational platforms, with business logic structured for reuse across multiple subject-oriented data marts. • Demonstrated ability to align architectural design decisions and implementation priorities to an enterprise data and analytics roadmap, including outcomes and priorities established through PI Planning. • Evaluate and optimize SQL MI-based Gold-layer structures for query performance, scalability, maintainability, and reuse, including appropriate indexing, partitioning, materialized views, aggregation strategies, and execution patterns. • Define reusable enterprise-level dimensions, measures, business rules, reference structures, and detailed data entities within the Gold/SQL MI layer to minimize duplication and promote consistent definitions across subject-oriented data marts. • Lead the data-model design and implementation approach for pending subject-oriented data marts identified in the enterprise roadmap, reusing common Gold-layer metrics, detail structures, dimensions, and business logic wherever practical. • Design and establish reusable Gold-layer metrics and detail layers in Azure SQL Managed Instance (SQL MI), including modular stored procedures, views, and materialized views that centralize business logic and can be leveraged across multiple subject-oriented data marts and reporting use cases. • Align architectural designs, technology choices, and technical decisions with the enterprise data and analytics roadmap established through PI Planning, ensuring near-term delivery decisions support th