Analytics Engineer - End-to-End Data Products & AI

Capital Factory; United States; On-site; USD 140,000 - 154,000; Full time

Benefits offered by this job

Hybrid work environment

401k match

Medical, dental, and vision benefits

Paid time off 19 days + 19 holidays

Flexible work schedule

Wellness programs

On-site space in a downtown Austin HQ

Weekly lunch, snacks

Job summary

Aceable is seeking a Sr Analytics Engineer who owns data products end to end—from source to dashboard—working closely with Marketing, Product, Finance and Engineering to deliver reliable, decision-ready data solutions.

You’ll design dbt models, semantic views, and AI-enabled data experiences in Snowflake, build Power BI dashboards, and implement testing, monitoring, and documentation to maintain data trust across the organization.

Qualifications

• 7+ years of experience in Analytics Engineering, Data Engineering, Business Intelligence Engineering, or a similarly technical data role.
• Advanced SQL and hands-on experience building production-scale transformations in a cloud data warehouse, ideally Snowflake, dbt, and GitHub or close equivalents
• A strong understanding of dimensional modeling, data marts, data quality testing, documentation, version control, code review, and software development lifecycle practices
• Experience with at least one data integration, ETL/ELT, orchestration, or event-data platform, plus a solid understanding of how data moves from source systems through transformation and into downstream reporting
• Experience building semantic models, DAX measurements, dashboards, and self-service data products using Power BI or an equivalent modern BI platform
• The ability and judgment to take a highly ambiguous business problem, ask the right questions, and turn it into something reliable and maintainable, plus the communication skills to do that with deeply technical partners and stakeholders who just need the data to make sense
• Experience building semantic layers, AI agents, or automated workflows that support generative AI and natural-language analytics and a willingness to use AI responsibly to accelerate technical work, automate repeatable processes, and continuously expand your capabilities

Responsibilities

• Own data products end to end. Take a problem from source data all the way through to the dashboard, metric, or workflow someone actually makes a decision with. Design, build, test, deploy, and maintain the whole path rather than handing it off at each layer.
• Turn fuzzy questions into things people trust. Work directly with partners in Marketing, Product, Finance, and Engineering to figure out what they're really asking, then build something reliable and maintainable enough that they stop asking you and just use it.
• Own quality from source to screen. Build the testing, documentation, monitoring, and data quality controls that keep trust high, and when something breaks, chase it wherever it actually lives: pipeline, transformation, model, metric, or report.
• Leave the platform better than you found it. Improve architecture, simplify workflows, and automate repetitive work, including using AI well to move faster on coding, investigation, testing, and documentation, while holding the line on accuracy and human review

Skills

Analytics engineering

Data engineering

BI engineering

Problem solving

AI experience

Tools

Snowflake

dbt

GitHub

Power BI

Matillion

Segment

Job description

Aceable is seeking a Sr Analytics Engineer who owns data products end to end—from source to dashboard—working closely with Marketing, Product, Finance and Engineering to deliver reliable, decision-ready data solutions.

You’ll design dbt models, semantic views, and AI-enabled data experiences in Snowflake, build Power BI dashboards, and implement testing, monitoring, and documentation to maintain data trust across the organization.