Lead Engineer — Reporting​/BI Engineering

About the Role

As a Lead Engineer in Reporting/BI Engineering, you will own the day-to-day technical leadership of a small scrum team focused on building and enhancing the reporting and business intelligence capabilities of the Certent Equity Management (CEM) platform for a large, strategic enterprise client engagement. Reporting to the Sr Engineering Manager, your responsibilities split between hands-on technical work and leading the team — setting priorities, unblocking teammates, running scrum ceremonies, and holding the team accountable for high-quality delivery.

You will also partner closely with the Sr Engineering Manager and interface directly with client stakeholders.

• Serve as the technical authority for your scrum team — making day-to-day engineering decisions, setting the bar for code quality, and ensuring the team delivers high-quality reporting solutions on schedule.
• Write, review, and contribute production-quality code across the BI and reporting stack — SQL, Oracle, and the application tier — as an active, hands-on member of the team.
• Lead sprint ceremonies as scrum master: planning, refinement, daily stand-ups, demos, and retrospectives.
• Set daily priorities for the team; actively unblock teammates by removing dependencies, clarifying requirements, and resolving technical ambiguity.
• Hold the team accountable to engineering standards — query performance benchmarks, code review discipline, definition of done, and release readiness.

• Diagnose and rebuild poorly performing SQL, including real-time data cube queries against non-flattened hierarchical data models, into optimized, maintainable, production-grade solutions.
• Lead Oracle query tuning and optimization initiatives: execution plan analysis, indexing strategies, materialized views, partitioning, and read-optimization patterns.
• Design and advocate for reporting data models and query architectures built for BI consumption — reducing real-time computation overhead and improving report responsiveness.
• Establish SQL quality standards for the team; drive adoption of query review practices and performance benchmarks as part of definition of done.

• Target ≥50% AI-authored pull requests and ≥95% AI code review adoption as minimums for your team.
• Model an agentic development mindset — integrating AI tooling into your own workflow and coaching teammates to do the same.
• Push the team beyond baseline AI adoption into workflows and practices that improve delivery velocity and reporting quality.
• Stay current on agentic development tooling and bring forward-looking recommendations to the Sr Engineering Manager.

• Directly manage four to five engineers, owning 1:1s, performance feedback, career development conversations, and day-to-day engagement.
• Partner with the Sr Engineering Manager on hiring decisions, onboarding, and performance management for the team.
• Identify and grow technical talent within your squad, coaching engineers on BI/SQL skills and professional development.
• Foster a collaborative, high-accountability culture that takes quality seriously and supports each other's success.

• Interface directly with client stakeholders on reporting requirements, asking the right questions, digging into root business problems, and challenging one-off solutions.
• Advocate for reporting solutions that solve the client's use cases while working generically across the broader CEM platform and client base.
• Partner with the Sr Engineering Manager and Product Management to ensure requirements are well-defined, properly scoped, and sequenced for delivery.
• Build credibility with client stakeholders through delivery consistency, clear communication, and a track record of solving the right problems.

• Coordinate with matrixed QA engineers to ensure test coverage, quality gates, and release readiness are met.
• Collaborate with Principal Engineers, the Solution Architect, and peer Lead Engineers on cross-team technical decisions and data architecture standards.
• Surface delivery risks,…