Analytics Engineer

About the role

The Analytics Engineer plays a crucial role in 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, build, and maintain 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
• Snowflake
• Azure Data Factory
• Data Modeling
• Data Transformation
• Data Visualization
• SQL
• DAX
• Kimball Data Modeling
• Medallion Architecture
• Automated Data Extraction
• 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.