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 the target-state architecture and long-term modernization objectives.

Requirements:

• BS degree in Computer Science or related field and 8+ years or Masters with 6+ years of experience
• 5+ years experience designing conceptual, logical, physical data models.
• 4+ years experience in cloud data architecture, including integration, data storage, query architectures.
• 4+ years developing and implementing data models for Microsoft SQL Server, star models, data marts, and SSAS OLAP cubes
• Experience developing and implementing models for data lake, Azure SQL and NoSQL databases
• Experience with design of data backup and retention, data migration, data quality
• Ability to work directly with client personnel at management and functional levels.
• Ability to clearly document, explain and obtain buy-in of designs and technical roadmap.
• Very strong SQL query language skills, with experience optimizing data query performance
• Knowledge and understanding of programming languages like Python, Spark, and .NET based development
• Knowledge and experience with data governance, including metadata management, enterprise data catalog, design standards, data quality governance, and data security.
• Experience with Agile process methodology, and CI/CD automation, and cloud based development (Azure, AWS).
• Ability to successfully obtain a government-issued Public Trust clearance.

• US Citizenship
Preferred Qualifications:

• Experience developing Master Data Management solutions
• Scaled Agile Framework (SAFe)
• Experience working with Azure DevOps
• Azure Enterprise Data Analyst certification
Candidate must be a U.S. citizen who has resided in the U.S. for at least 3 years and the ability to obtain a public trust
10% travel is estimated to be required.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.