Director, Business Intelligence and Data Engineering

The Lisinski Law Firm

6d•$176,000 - $229,000

About The Position

Lisinski Law Firm is seeking a visionary and hands-on Director of Business Intelligence & Data Engineering to transform how data is managed, governed, and leveraged across the organization. This is a build-and-lead opportunity to design and build the firm's modern data ecosystem from the ground up, creating the architecture, governance, reporting capabilities, and analytics strategy that will enable leaders to make smarter, faster, and more informed decisions. The role will oversee both Data Engineering and Business Intelligence functions, building a team, establishing best practices, and creating a scalable foundation that supports the firm's continued growth.

Requirements

Bachelor's degree in Computer Science, Data Engineering, Information Systems, Statistics, or a related field.
10–15 years of progressive experience in Data Engineering, Business Intelligence, Analytics, or related disciplines.
7+ years of leadership experience managing technical teams and driving large-scale data initiatives.
Proven experience designing and building a data warehouse or data lakehouse—not simply managing an existing environment.
Strong expertise in SQL and at least one data engineering programming language (Python preferred).
Experience with cloud-based data platforms such as Azure, AWS, GCP, Snowflake, Databricks, or comparable technologies.
Strong understanding of data governance, data quality management, metadata management, and enterprise reporting.
Exceptional ability to communicate complex technical concepts to executive and non-technical audiences.

Nice To Haves

Master's degree in a related technical field.
Experience integrating data across CRM platforms (Salesforce preferred), financial systems, HRIS, telephony systems, and SaaS applications.
Experience in high-growth, operationally complex organizations.
Legal industry experience is a plus, but not required.
Experience building data organizations and processes in environments where data infrastructure was previously immature or fragmented.

Responsibilities

Design and implement a modern data warehouse or data lakehouse architecture from the ground up.
Evaluate and select the best-fit technologies, platforms, and tools based on organizational needs.
Build scalable data pipelines that connect critical business systems including Salesforce/Litify, telephony platforms, financial applications, HR systems, and third-party SaaS solutions.
Establish automated, repeatable ETL/ELT processes that improve efficiency, reliability, and scalability.
Create and implement a comprehensive data governance framework, including KPI definitions, metric standards, data dictionaries, and ownership models.
Establish data quality standards and processes that identify, measure, and remediate data integrity issues across the organization.
Drive consistency and trust in reporting by creating a single source of truth for business metrics and operational reporting.
Develop practices that ensure compliance with privacy, security, and regulatory requirements.
Design and deliver executive dashboards and operational reporting that drive decisions.
Partner with business leaders to translate strategic questions into meaningful metrics, analytics, and reporting solutions.
Build proactive analytics capabilities that identify trends, risks, opportunities, and performance drivers.
Elevate the organization from reactive reporting to predictive and insight-driven decision-making.
Lead a combined Business Intelligence and Data Engineering organization.
Hire, mentor, and develop technical talent while fostering a culture of accountability, innovation, and continuous improvement.
Establish team goals, roadmaps, and measurable quarterly outcomes aligned with business priorities.
Reduce operational risk by building scalable processes and eliminating single points of failure.
Collaborate with executive leadership, department leaders, and technology stakeholders to align data strategy with firm objectives.
Work closely with the VP of IT/CIO and peer technology leaders to ensure data architecture aligns with broader technology initiatives.
Serve as a trusted advisor who can translate complex technical concepts into clear, business-focused recommendations and insights.