Business Data & Process Analyst

Johns Hopkins Applied Physics Laboratory•Laurel, MD

2d•Onsite

About The Position

APL is seeking a Business Data & Process Analyst to help modernize the way financial and operational information is structured, leveraged, and used across the organization. In this role, you will help drive the transition from legacy reporting solutions to a scalable enterprise data environment that supports informed decision-making and trusted analytics. You will operate at the intersection of business operations, financial oversight of government contracts, and enterprise data strategy. You will break down complex legacy information, translate operational needs into data requirements, and support building the foundation for future analytics capabilities. The successful candidate will be curious, and motivated by continuous improvement. This role offers the opportunity to influence enterprise initiatives, improve business transparency, and contribute to solutions that deliver lasting organizational value.

Requirements

Bachelor's degree in Information Systems, Computer Science, Accounting, Finance, or a related field.
Three or more years of experience supporting the financial management of government contracts, with knowledge of project accounting principles, contract reporting, and related business operations.
Demonstrated business process analysis skills, including the ability to document current-state processes, define future-state workflows, and create process maps using process flow and process modeling tools.
Excellent written communication skills, with the ability to translate business and reporting requirements into clear, well-documented data requirements, business rules, and transformation logic.
Proficiency in data analysis, data mapping, and source-to-target analysis.
Advanced Microsoft Excel skills, including PivotTables and techniques for large-scale data analysis, with the ability to validate, reconcile, and analyze detailed financial and operational datasets.
Experience with Oracle E-business Suite or similar enterprise financial systems.
Experience working with enterprise data platforms, including data warehouses and data virtualization technologies (e.g., Denodo), to analyze, validate, and interpret business data.
Strong analytical and problem-solving skills, with the ability to translate complex business needs into clear requirements and build consensus among business and technical stakeholders.
Demonstrated ability to lead small projects, facilitate workshops, and foster multi-functional collaboration.

Nice To Haves

Master's degree in Management Information Systems, Business Adminstration, or other related degree.
Business Analyst certification (e.g., CBAP®, CCBA®, PMI-PBA®, or equivalent).
Proficiency with SQL for data analysis, validation, solving problems, and data quality investigations.
Familiarity with Power Query and Power BI to support data transformation, visualization, and delivery of business insights from enterprise data sources.
Knowledge of data governance practices, including data definitions, metadata management, and tools such as Collibra.
Understanding of Agile methodologies and participation in Agile delivery teams and processes.
Knowledge of enterprise data modernization initiatives, including reporting transformation and legacy system retirement efforts.

Responsibilities

Analyze and document current-state business processes related to government contract financial management, including contract structures, funding, labor, revenue, cost, and staffing.
Look for opportunities to simplify, improve, and modernize workflows while supporting enterprise data objectives.
Translate business processes, reporting logic, and operational needs into clear business rules, data requirements, and transformation specifications.
Partner with customers across finance, operations, technology, and data teams to establish shared understanding of business and data requirements.
Collaborate with data engineers and developers to support data modeling, ETL design, testing, and validation activities.
Analyze complex financial and operational datasets to identify trends, inconsistencies, data quality issues, and improvement opportunities.
Validate data accuracy and business logic as legacy reporting systems are transitioned to modern enterprise platforms.