Analytics Data Engineer II

Location: City of Rochester

Butler/Till is a results-driven marketing agency offering deeply collaborative client experiences, proprietary technology, and world-class partnerships. At Butler/Till, we take immense pride in our independent, women-owned and led status, our unwavering commitment to a purpose-driven approach, our B-Corp status, and our unique structure as a 100% employee-owned company (ESOP).

SUMMARY

The Analytics Data Engineer II designs, builds, and maintains scalable data solutions—including data marts, pipelines, and automated workflows that power reporting and advanced analytics. This role applies strong SQL, Python, and cloud‑platform expertise to deliver reliable, well‑governed data that supports decision‑making and operational efficiency. The position also drives data quality, documents and standardizes processes, strengthens platform security, and contributes to team growth through mentorship and technical guidance.

KEY

OUTCOMES & RESPONSIBILITIES Key Outcome:
Streamlined Data Management & Productivity:
Deliver reliable, well-structured data that improves efficiency, automates workflows, and enables faster, more informed decision-making across the organization.

Key Responsibilities:

• Partner with managers and internal and external stakeholders to capture requirements and architect, standardize, scope, and document Butler/Till data frameworks.
• Design, build, and automate scalable, standardized, and client-specific data marts to support consistent reporting and analytics delivery.
• Collaborate cross-functionally to develop data solutions that streamline workflows and improve operational efficiency.
• Work closely with Analytics, Media, and Account teams to understand client data needs and drive standardized campaign and ad naming conventions.
• Maintain comprehensive documentation for data policies, data dictionaries, metadata, and ETL processes to ensure transparency, consistency, and continuity.

Key Outcome:
Increased Reliability:
Deliver trusted, accurate, and well-governed data through consistent processes and quality controls, enabling teams to make confident decisions and quickly respond to performance insights and evolving business needs.

Key Responsibilities:

• Serve as the first line of defense for data integrity by executing and continuously improving quality assurance and validation processes.
• Partner with Analytics teams to resolve data-related tickets, troubleshoot issues, and ensure timely, accurate file processing.
• Maintain and optimize third-party monitoring tools that detect data inconsistencies, gaps, and failures, triggering rapid corrective action.
• Act as a subject matter expert on Butler/Till data marts and key marketing platforms (e.g., Google, Meta), ensuring data is correctly interpreted and applied across Campaign Analytics and Marketing Science.
• Mentor junior Analytics Data Engineers on QA standards and best practices through structured code reviews and ongoing technical guidance.

Key Outcome:
Reduced Risk:
Protect the organization from data loss, misuse, and breaches by enforcing strong security, access controls, and backup standards that ensure business continuity, regulatory compliance, and the secure handling of sensitive information.

Key Responsibilities:

• Maintain working knowledge of applicable data privacy and protection regulations (e.g., CCPA, GDPR) and incorporate requirements into daily data practices.
• Consistently follow and help enforce organizational policies, security standards, and governance frameworks across all supported data processes.
• Review, analyze, and troubleshoot data pipelines, processes, and database code to identify vulnerabilities, mitigate risks, and strengthen security controls.

Key Outcome:
Scalability:
Enable efficient growth by building standardized, repeatable data processes that reduce operational overhead and support expanding client and business needs.

Key Responsibilities:

• Prepare data for reporting, analysis, and modeling by building repeatable, client-specific data marts in partnership with Information Analysts and Data Scientists.
• Leverage SQL and Python to design and maintain scalable, end-to-end data solutions that support evolving business needs.
• Identify and…