Analytics Engineer

About the role

The Analytics Engineer is responsible for designing, building, and maintaining the organization’s analytics and business intelligence solutions. This role bridges the gap between raw data and business decision-making by developing reliable semantic models, scalable Power BI dashboards, and actionable insights across multiple data platforms.

Responsibilities

• Design and build Power BI dashboards and reports that provide clear, actionable insights to business stakeholders.
• Develop and manage semantic data models optimized for analytics, performance, and self-service reporting.
• Translate business questions and requirements into analytical solutions, KPIs, and metrics.
• Analyze trends, patterns, and anomalies in data and clearly articulate findings to technical and non-technical audiences.
• Develop and maintain analytics solutions using Snowflake (Data Warehousing).
• Integrate and analyze data from multiple sources, including Snowflake, line-of-business systems, and cloud platforms.
• Partner with other data engineers and system owners to ensure data structures support accurate and performant reporting.
• Optimize data models and queries for performance, scalability, and cost efficiency.
• Ensure consistency and accuracy of KPIs, metrics, and definitions across reports and dashboards.
• Implement data security practices such as row-level security (RLS) and appropriate access controls.
• Document data models, reporting logic, and metric definitions to support transparency and maintainability.
• Support data governance and reporting standards across the organization.
• Collaborate with business stakeholders to understand reporting needs and drive data-informed decision-making.
• Quickly gain sufficient understanding of the business to recognize Analytics needs, gaps in solutions, & processes/stakeholders to involve – independent of significant support.
• Enable self-service analytics while maintaining a trusted, centralized source of truth.
• Provide guidance and best practices for Power BI usage, dashboard design, and analytics workflows.
• Contribute to ongoing analytics and data platform improvements as the organization matures its data capabilities.
• Drive adoption of the reports you produce through trainings, relevance-iterations, & inserting reports into critical business decision processes.
• Own analytics initiatives from intake through delivery, including requirements prompting & clarification, effort estimation, sequencing work, and managing dependencies.
• Translate business questions into scoped, well-defined analytical deliverables with clear criteria and metric definitions.
• Plan and execute work to meet agreed-upon timelines while proactively identifying turnaround risks and tradeoffs.
• Maintain clear communication with stakeholders on progress, blockers, and changes in project plans.
• Estimate cost, effort, and complexity for analytics work to support capacity planning and prioritization.
• Design scalable, efficient data models and pipelines with awareness of compute, storage, and tooling costs.
• Consistently deliver analytics solutions on schedule and aligned to business expectations.
• Break large initiatives into phases or milestone-based releases when appropriate.
• Incorporate stakeholder feedback recognizing and communicating anytime it may be jeopardizing timelines or data integrity.

Requirements

• 3+ years of experience in analytics, business intelligence, or analytics engineering.
• Strong past experience in at least 8 of these tools/languages/concepts: Snowflake (Data Warehousing), DBT (Data Transformations), Azure Data Factory (Data Orchestration & Extraction), Power BI (Data Visualization), SQL (Data Transformations), DAX (Data Transformations/Visualizations), Kimball Data Modeling (Data Transformations), Medallion Architecture (Data Transformations), Automated Data Extraction (Sourcing from ODBC, APIs, Files, Connectors, etc), Utilizing AI in Data Engineering & Analysis.
• Strong hands-on experience with Power BI, including but not limited to: Data modeling, DAX, Power Query (M), Dashboard and report design.
• Experience working with Snowflake or modern analytics platforms.
• Experience integrating and analyzing data from cloud data platforms such as Snowflake.
• Experience working with Azure Data Factory and/or Microsoft Fabric Data Factory.
• Strong SQL skills and solid understanding of relational and analytical data modeling concepts.
• Proven ability to analyze data and clearly communicate insights to business stakeholders.
• Must be a team player who takes a “we over me” approach to building and sustaining relationships with others.
• Strong documentation, organization, and communication skills; must be proficient in speaking, reading, and writing in English.
• Valid driver’s license and insured, operable vehicle.

Qualifications

• High School diploma or equivalency certificate.

Skills

• Power BI (Data Visualization)
• Snowflake (Data Warehousing)
• Azure Data Factory (Data Orchestration & Extraction)
• DBT (Data Transformations)
• Kimball Data Modeling (Data Transformations)
• Medallion Architecture (Data Transformations)
• Automated Data Extraction (Sourcing from ODBC, APIs, Files, Connectors, etc)
• Utilizing AI in Data Engineering & Analysis

Benefits

• Competitive pay, $100,000 - $140,000 per year (based on experience).
• Annual bonus incentive.
• Annual performance review with potential merit increase.
• Medical, Dental, & Vision insurance - with 100% employer paid monthly premiums for associates.
• Flexible Spending Accounts- for healthcare and dependent care.
• Disability, AD&D, and Life insurance.
• 401(k) with 3% company contribution.
• Accrued vacation time, sick pay, 12 paid holidays per calendar year, personal day, and paid volunteer day.
• Employee Assistance Program.
• Charitable giving program and community involvement.

Physical Requirements

• Sitting: 2-7 hours/day.
• Walking: 1-2 hours/day.
• Climbing (stairs): 1-3 hours/day.
• Lifting: 20-40 lbs. regularly.
• Endurance: light to moderate energy requirements.
• Manual Dexterity: frequent fine motor skills.
• Near Vision: minimal near vision.

Environmental and Safety Factors

• Weather: work is primarily indoors in a temperature-controlled office environment with occasional exposure to outdoor weather conditions, including uneven and slippery surfaces.
• Noise: frequent exposure to typical office environment noise levels including conversational voice levels; infrequent exposure to high-volume office equipment (e.g., shredder).
• Pace of Work: great, multi-tasking/pressure paced environment.