Data and Power BI Engineer

Modern Family Law•Washington, DC

1d•Remote

About The Position

Modern Family Law is seeking a Data & BI Engineer to own and evolve the firm’s Power BI semantic model, strengthen our data infrastructure, and position the firm for AI-driven decision-making. This role bridges business intelligence, data engineering, and IT collaboration, ensuring data is accurate, scalable, secure, and actionable. The Data & BI Engineer will partner closely with Finance, IT, Operations, and firm leadership to translate business needs into reliable reporting, scalable data models, automated pipelines, and actionable insights. This role is critical to building the firm’s single source of truth and preparing the organization for future AI, automation, predictive analytics, and data-driven decision-making. This role is fully remote and requires the ability to work independently, proactively, and with a high degree of ownership.

Requirements

4+ years of experience in business intelligence, data analytics, data engineering, analytics engineering, or a similar data-focused role.
Strong hands-on experience developing Power BI reports, dashboards, datasets, and semantic models.
Experience with DAX, Power Query/M, and data modeling best practices.
Experience building or maintaining data models for reporting and analytics.
Experience working with data pipelines, dataflows, APIs, SQL sources, cloud applications, or similar data integrations.
Ability to gather business requirements and translate them into clear reporting, dashboard, and data solutions.
Strong analytical, troubleshooting, and problem-solving skills.
Strong communication skills and ability to work with technical and non-technical stakeholders.
Ability to work independently in a remote environment with a high degree of ownership and accountability.
Ability to communicate verbally and in writing using a telephone, text messaging, or email
Ability to sit for extended periods of time at a desk while typing, using a mouse, and looking at a computer screen
Ability to stand, sit, bend, and lift items up to 10 lbs as needed

Nice To Haves

Experience with Microsoft Fabric, lakehouses, or similar modern data platforms.
Experience designing star schema data models.
SQL experience for querying, validation, troubleshooting, or transformation.
Python experience for API calls, automation, or pipeline scripting.
Familiarity with Azure ecosystem tools.
Familiarity with AI readiness, predictive analytics, machine learning concepts, or automation use cases.
Experience working with Salesforce, financial systems, legal technology platforms, or practice management systems.
Experience building KPI frameworks, executive dashboards, or finance/operations reporting.
Experience working in a law firm, professional services, or multi-state business environment.
Bachelor’s degree in Data Analytics, Computer Science, Information Systems, Business Intelligence, Finance, Engineering, or a related field preferred.
Equivalent hands-on experience, certifications, or technical training may be considered in lieu of formal education.
Strong systems thinking with the ability to understand and optimize complex workflows.
Strong process design and optimization capabilities.
Ability to structure and interpret data to drive decision-making and performance improvements.
Ability to communicate professionally and interact effectively with all levels of personnel, including executives, management, attorneys, and support staff.
Ability to be a proactive self-starter who understands the details within a much larger business context.
Demonstrated attention to detail, reliability, and ability to quickly learn new technology.
Excellent organizational and prioritization skills, with the ability to manage multiple initiatives simultaneously.
Ability to be a proactive self-starter who understands the details within a much larger context
Flexibility and ability to respond quickly and positively to shifting demands.
Ability to work under pressure and meet deadlines in a fast-paced environment.
Strong judgment regarding confidentiality, data integrity, and sensitive business information.

Responsibilities

Own, maintain, and enhance the firm’s Power BI reporting environment, dashboards, reports, datasets, and semantic model.
Design and maintain scalable data models, including star schema models and standardized reporting structures.
Build, maintain, and troubleshoot data pipelines across internal and external systems.
Ingest, clean, structure, and validate data from APIs, SQL sources, cloud storage, Salesforce, financial systems, and other business platforms.
Partner with Finance, IT, Operations, and firm leadership to define business requirements, KPIs, reporting logic, and data definitions.
Ensure data accuracy, consistency, quality, documentation, and appropriate governance.
Support AI readiness by preparing structured, reliable data for automation, predictive analytics, and future AI-driven insights.
Support system integrations and data-related troubleshooting as needed.
Gather, document, and interpret reporting requirements from business stakeholders.
Translate business needs into scalable data, reporting, dashboard, and analytics solutions.
Partner with stakeholders to clarify definitions, reporting logic, priorities, and expected outcomes.
Help business leaders understand what the data is showing and how it can be used to support decision-making.
Build, maintain, and enhance Power BI reports and dashboards.
Own and maintain the Power BI semantic model as the firm’s single source of truth.
Manage and optimize the Power BI Service ecosystem, including workspaces, access, deployments, refresh schedules, and reporting governance.
Optimize reporting performance, usability, accuracy, and scalability.
Maintain consistency across dashboards, reports, calculations, and firm-wide metrics.
Design and implement star schema data models.
Build scalable, high-performance data structures for reporting and analytics.
Establish consistent data definitions, relationships, calculations, and documentation.
Ensure data models are structured in a way that supports current reporting needs and future AI or automation use cases.
Make API calls to ingest data from internal and external systems.
Move, structure, and maintain data within Microsoft Fabric lakehouses.
Maintain and extend existing data pipelines.
Ensure reliability, performance, and data quality across pipelines.
Use Power Query and M code for data shaping, cleaning, and transformation.
Tune performance through query folding, data profiling, and model optimization.
Connect to and integrate diverse data sources, including SQL, APIs, cloud storage, Salesforce, financial systems, and other platforms.
Establish and maintain processes for cleansing, deduplicating, and standardizing data.
Ensure consistent definitions, mappings, and synchronization across key business systems.
Prepare structured data for AI and automation use cases.
Support development of predictive analytics and AI-driven insights.
Partner with leadership on AI opportunities and data strategy.
Help identify practical, business-focused AI use cases that can improve reporting, efficiency, and decision-making.
Ensure data is organized, documented, and reliable enough to support future AI initiatives.
Collaborate closely with the CFO and Finance team to define, standardize, and maintain core business metrics and KPIs.
Translate financial and operational goals into scalable data models and reporting logic.
Collaborate with Finance, Operations, IT, and other teams to support reporting and systems initiatives.
Support system integrations and data-related troubleshooting.
Contribute to broader IT and systems initiatives as needed.
Support the development and maintenance of firm-wide data governance practices.
Maintain documentation for data definitions, data sources, reporting logic, ownership, and refresh schedules.
Ensure appropriate data access, security, and confidentiality controls within reporting tools.
Promote consistency and trust in firm-wide reporting.
Partner with IT and Finance to ensure sensitive financial, employee, operational, and client-related data is handled appropriately.