Business Intelligence Engineer

Leader Bank•Arlington, TX

4d•$100,000 - $120,000•Onsite

About The Position

Leader Bank is looking for exceptionally dedicated team members to join one of the region’s fastest growing community banks and mortgage lenders. At the time of its founding in 2002, Leader Bank had one branch office, $6.5 million in assets and 7 team members. Since then, the Bank has become one of the most successful banks in Massachusetts with $4.5 billion in assets, more than 400 team members, 7 branch offices, and annual mortgage originations of over $2 billion. Exemplary products and an innovative spirit have driven Leader Bank’s rapid growth over the years, and our team members embrace these values. Our mission is to obsess over our clients, make them feel valued, and maintain long-term relationships with them by constantly enhancing our products and processes to always improve our client experience. For our team members, Leader Bank prioritizes competitive compensation and benefits, a healthy work-life balance, and an environment that fosters diversity and inclusion. Summary At Leader Bank, we recognize that data is an opportunity to create better experiences, smarter decisions, and value for our clients. As a BI engineer, you enable stakeholders to make data-driven decisions and turn insights into action through automation. BI Engineer is responsible for designing, developing, and maintaining the Bank's enterprise reporting and analytics platform. This role bridges business reporting and data engineering by creating trusted data models, semantic layers, dashboards, and analytics solutions that empower data-driven decision-making across the organization. The successful candidate will have deep experience with Snowflake, Retool/Power BI, Python, JavaScript, SQL, and modern data technologies. This individual will partner with business stakeholders, product teams, and technology teams to transform raw data into trusted, actionable insights while establishing scalable reporting and governance practices.

Requirements

Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field.
3+ years of experience in Business Intelligence, Data Engineering, Analytics Engineering, or related disciplines.
3+ years of hands-on experience with Snowflake or other relational databases.
3+ years of experience building dashboards and analytics solutions using Power BI/Tableau/Retool or similar BI platforms.
Strong SQL expertise including performance optimization, dimensional modeling, and data warehouse design.
Strong Python programming experience for analytics, automation, and data processing.
Experience with JavaScript for dashboard customization, application development, and automation.
Experience building and maintaining ETL/ELT pipelines.
Knowledge of data governance, metadata management, and data quality principles.
Experience working with Git, CI/CD pipelines, and Agile development practices.

Nice To Haves

Experience with dbt, Matillion or similar modern data stack technologies.
Experience working in banking, financial services, fintech, or regulated industries.
Familiarity with cloud platforms such as AWS.
Knowledge of API development and integrations.
Experience leveraging AI and machine learning tools to improve analytics and reporting.
Snowflake, Power BI, or cloud certifications.

Responsibilities

Data Modeling & Analytics: Design, develop, and maintain enterprise data models, semantic layers, and analytics-ready datasets in Snowflake. Build and maintain data dictionaries, KPI definitions, and business metrics to ensure consistency across reporting platforms. Develop scalable reporting architectures that support operational, analytical, and executive reporting needs. Optimize data structures, queries, and warehouse performance for BI workloads.
Reporting & Visualization: Create and maintain dashboards, workflows and self-service reporting solutions using Retool, and other BI tools. Partner with business stakeholders to understand requirements and translate business questions into actionable analytics. Develop executive-level dashboards and operational reporting that provide meaningful business insights. Ensure data visualizations are intuitive, accurate, and aligned with organizational goals.
Data Engineering & Automation: Develop and maintain ELT/ETL processes for structured and semi-structured data. Build automated data validation, quality monitoring, and reconciliation processes. Utilize Python, SQL, and JavaScript to automate reporting, data transformations, and analytics workflows. Collaborate with Data Engineers to enhance data ingestion, transformation, and governance frameworks.
Governance & Quality: Establish and maintain data quality standards, validation rules, and monitoring processes. Define and enforce data governance best practices, metadata management, and documentation standards. Ensure compliance with security, privacy, and regulatory requirements. Promote adoption of trusted data sources and standardized reporting practices.
Collaboration: Work closely with business leaders, product managers, analysts, and engineering teams. Participate in Agile planning, estimation, and solution design activities. Provide guidance on analytics best practices, dashboard design, and data storytelling.