Sr Analytics Engineer
About The Position
Aceable is seeking a hands-on Senior Analytics Engineer to join a small team working across Data Engineering and Business Intelligence. The role owns high-visibility data architecture and pipeline problems end to end, from source data through transformations and models to dashboards, metrics, or workflows used for decisions. Work may include building and troubleshooting data pipelines, designing dbt models and semantic views, creating AI agents in Snowflake, building Power BI dashboards, and collaborating with stakeholders to turn business questions into trusted data products. The position calls for technical depth across multiple areas, strong problem-solving skills, experience and enthusiasm for AI, and curiosity about unfamiliar tools and challenges. The successful candidate will work with partners across Marketing, Product, Finance, Engineering, and other teams to develop reliable, maintainable data products and improve the data platform through better architecture, automation, testing, documentation, monitoring, and quality controls. Aceable’s Business Intelligence & Data Engineering team supports data products spanning ingestion and event instrumentation, cloud data infrastructure, transformation and modeling, business intelligence, self-service analytics, and AI-enabled data experiences. The team is small and collaborative, with an emphasis on end-to-end ownership and close partnership across the company. The work environment is currently hybrid, with flexibility to work in the office or remotely depending on role, department, and location. Remote employees may be hired only in the states listed in the posting.
Requirements
- 7+ years of experience in Analytics Engineering, Data Engineering, Business Intelligence Engineering, or a similarly technical data role.
- Advanced SQL skills and hands-on experience building production-scale transformations in a cloud data warehouse; Snowflake, dbt, and GitHub or close equivalents are preferred in the posting.
- 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, and a solid understanding of how data moves from source systems through transformation into downstream reporting.
- Experience building semantic models, DAX measures, dashboards, and self-service data products using Power BI or an equivalent modern BI platform.
- Ability and judgment to clarify highly ambiguous business problems and turn them into reliable, maintainable solutions.
- Communication skills to work with deeply technical partners and stakeholders who need data to make sense.
- Experience building semantic layers, AI agents, or automated workflows that support generative AI and natural-language analytics.
- Willingness to use AI responsibly to accelerate technical work, automate repeatable processes, and continuously expand capabilities.
Nice To Haves
- Hands-on experience with Matillion or Segment.
- Experience supporting digital event instrumentation and transforming customer journey, product usage, and marketing data into trusted, analytics-ready datasets, particularly for Marketing, Product, Finance, or executive decision-making.
- Familiarity with APIs, JSON, Python, Git, CI/CD, and automated deployment workflows.
- Experience with data observability, lineage, governance, privacy, role-based access, and warehouse cost optimization.
Responsibilities
- Own data products end to end, from source data through to dashboards, metrics, or workflows used for decisions.
- Design, build, test, deploy, and maintain complete data solutions rather than handing work off at each layer.
- Partner with Marketing, Product, Finance, Engineering, and other stakeholders to clarify business questions and build reliable, maintainable data products.
- Build testing, documentation, monitoring, and data quality controls to maintain trust in data products.
- Investigate and resolve issues across pipelines, transformations, models, metrics, and reports.
- Improve data architecture, simplify workflows, and automate repetitive work.
- Use AI to accelerate coding, investigation, testing, and documentation while maintaining accuracy and human review.
- Support data ingestion and event instrumentation, cloud data infrastructure, transformation and modeling, BI, self-service analytics, and AI-enabled data experiences.
Benefits
- Competitive total rewards, including base salary and bonus/stock options, if applicable.
- 401(k) match.
- Medical, dental, and vision benefits.
- Generous paid time off programs and 19 paid holidays per year.
- Flexible work schedule.
- Wellness programs.
- Free parking at the downtown Austin office.
- Weekly lunch, a fully stocked fridge, and snacks.
- Company events and activities, including holiday events, happy hours, and volunteering.
- #PursueGrowth reimbursement of $600 per year for full-time employees.
- Free Roadside Assistance subscription.
- Hybrid work environment with flexibility to work in office or remotely based on role, department, and location.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
