You will bring an AI-first mindset — not just complying with organizational AI adoption targets, but genuinely integrating agentic development tooling into how you and your team work every day.
Responsibilities
Technical Leadership & Delivery
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 standups, 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.
SQL & Reporting Performance
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 that are 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.
AI-First Engineering
Champion ≥50% AI-authored PR targets and ≥95% AI code review adoption as organizational minimums for your team.
Model an agentic development mindset — integrating AI tooling into your own daily workflow and actively coaching teammates to do the same.
Push the team beyond baseline AI adoption into workflows and practices that measurably improve delivery velocity and reporting quality.
Stay current on agentic development tooling and bring forward-looking recommendations to the Sr Engineering Manager.
Team Leadership & People Management
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 your team.
Identify and grow technical talent within your squad — coaching engineers on both BI/SQL technical skills and professional development.
Foster a collaborative, high-accountability team culture that takes quality seriously and supports each other's success.
Client Engagement & Requirements
Interface directly with client stakeholders on reporting requirements — asking the right questions, digging into root business problems, and challenging requests that represent one-off solutions rather than platform-generic capabilities.
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 reporting 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.
Cross-Functional Collaboration
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, technical blockers, and scope concerns to the Sr Engineering Manager early and clearly.
Qualifications
Required
8-10+ years of hands-on software engineering experience with a strong specialization in BI, reporting, and SQL development in enterprise SaaS environments.
Deep Oracle SQL and PL/SQL expertise — query tuning, execution plan optimization, indexing strategies, materialized views, and large dataset performance optimization.
Demonstrated experience diagnosing and rebuilding poorly performing SQL against complex, non-flattened relational data models — including real-time reporting query optimization.
Hands-on experience with enterprise BI tooling — Power BI, Tableau, Cognos, or similar — with the ability to design effective reporting solutions against complex data models.
Demonstrated experience in a technical lead or lead engineer capacity — setting priorities, running ceremonies, and holding teammates accountable.
Demonstrated AI-first engineering mindset — hands-on experience with agentic development tooling (GitHub Copilot, Devin.AI, or similar) and a track record of driving AI adoption within an engineering team.
Experience with direct people management responsibilities — performance feedback, career development, and team engagement for a small team of engineers.
Familiarity with Microsoft technology stack — C#, .NET, and Azure cloud services — sufficient to engage in full-stack technical discussions.
Strong code review discipline and engineering quality standards — including SQL review, query performance benchmarking, and definition-of-done rigor.
Fluent communicator — able to engage credibly and directly with client stakeholders on complex reporting requirements and translate technical realities clearly.
Experience working in global, distributed teams across multiple time zones.
Bachelor's degree in Computer Science, Engineering, or equivalent work experience.
Preferred
Direct hands-on experience with Logi Analytics (now Logi Symphony) — this is a significant differentiator.
Experience designing data cube architectures and pre-aggregation strategies to reduce real-time query load on non-flattened hierarchical data models.
Experience with Oracle read-optimization patterns — materialized views, query rewrite, result cache, and analytical functions.
Familiarity with Azure cloud data services and cloud-native reporting patterns.
Background in financial services, equity compensation, or adjacent regulated domains where reporting accuracy and auditability are critical.
Certified Scrum Master (CSM) or equivalent Agile certification.
Experience mentoring mid-level engineers into senior or lead roles.
The salary range in United States of America for this position is 124,000.00 to 156,000.00 USD Annual.
Your specific offer within this range will be determined by your skills, experience, and qualifications. For non-sales roles, you may be eligible for a bonus. For sales roles, this range includes a commission target.
We are committed to pay transparency and fair compensation practices. If you have questions about our compensation approach, please don't hesitate to ask during the interview process.
Additional Information
All your information will be kept confidential according to EEO guidelines.
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