Analytics Engineer

RollKall Technologies, LLC•Irving, TX

6h•Hybrid

About The Position

RollKall is seeking an experienced Analytics Engineer to join our Business Intelligence team and shape the foundation of our analytics infrastructure. You'll build and maintain high-quality data pipelines, establish best practices for data transformation and validation, and drive adoption of AI-powered tools — all while building the dashboards and reports our stakeholders depend on. This role bridges data engineering and business intelligence, with a tech stack that includes Domo (cloud data warehouse and visualization), SQL Server, and Azure Logic Apps for third-party integrations. This position offers the opportunity to shape RollKall's analytics infrastructure — you won't just be building reports, you'll be driving enhancements to quality standards, documentation practices, and AI strategy that will scale our BI capabilities as we grow. The ideal candidate sees data quality as a strategic advantage, not a compliance checkbox, and is excited about building systems that make reliable data accessible to the entire organization and RollKall's customer base.

Requirements

Demonstrated experience owning data quality initiatives and implementing validation frameworks
Proven track record of building technical documentation and establishing process standards
Experience working independently and taking full ownership of projects from requirements through delivery
5-7 years of hands-on experience in analytics engineering, business intelligence, data analytics, or related roles.
BI Platform Experience: Strong experience with at least one modern BI platform (Domo strongly preferred; Tableau, Power BI, or similar platforms acceptable)
ETL/Data Transformation: Hands-on experience building and maintaining ETL/ELT pipelines and data transformation workflows
Data Modeling: Solid understanding of dimensional modeling, data warehousing concepts, and analytics-ready data structure
Version Control: Experience with GitHub for code repository management
SQL Expertise: Advanced SQL skills, including query optimization, performance tuning, complex joins, and window function optimization
Excellent communication skills with the ability to translate technical concepts for non-technical audiences
Strong analytical and problem-solving abilities
Ability to work effectively with remote team members and collaborate across departments
Self-motivated with the ability to identify and drive process improvements proactively
Experience balancing multiple priorities and managing stakeholder expectations

Nice To Haves

Direct experience with Domo platform (Magic ETL, Dataflows, Beast Modes, Domo administration)
Familiarity with Azure cloud services and Logic Apps
Experience with AI/ML tools in analytics contexts
Background in SaaS, municipal government, or public safety sectors
Proficiency with object-oriented programming (Python, .NET, or similar)
Knowledge of JSON and YAML
Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field

Responsibilities

Design and implement data quality frameworks, including validation rules, testing procedures, and monitoring systems to ensure data accuracy and reliability
Build and maintain comprehensive technical documentation for all data assets, including data dictionaries, transformation logic, business rules, and data lineage
Enforce analytics engineering best practices and standards across the BI environment
Proactively identify and resolve data quality issues, conduct root cause analysis, and implement preventive measures
Champion data governance initiatives and serve as the quality advocate for the BI team
Design, develop, and optimize data transformations using Domo's Magic ETL (both visual dataflows and SQL)
Build scalable, performant data models that serve as the foundation for reporting and analytics
Create and maintain Domo dashboards, cards, and visualizations based on business requirements
Manage Domo platform administration, including user access, dataset schedules, and dataflow performance optimization
Develop and automate reports and scheduled deliveries to support business operations
Collaborate with stakeholders to gather requirements, translate business needs into technical solutions, and deliver actionable insights
Troubleshoot data discrepancies and performance issues across the analytics stack
Evaluate Domo's AI capabilities and help develop a roadmap for adopting AI-powered features that enhance data quality, self-service analytics, and business insights
Leverage existing AI tools (eg, Claude Code) to accelerate documentation creation and improve data discovery
Champion the strategic use of AI within the BI environment to drive efficiency and innovation
Stay current with emerging analytics engineering trends and Domo platform developments