Siepe2mo ago

Senior Manager, SQL Development

Dallas · DallasFull-timesenior

Development ManagerConstruction & Real Estate

0 views0 saves0 applied

Apply Now

Quick Summary

Requirements Summary

you will standardize how AI is used across the Professional Services organization—creating repeatable, safe, high-leverage AI workflows that increase throughput without sacrificing correctness,

Technical Tools

Development ManagerConstruction & Real Estate

Siepe is a fast-growing technology company headquartered in Dallas, TX – focused on helping investment managers turn complexity into clarity. We build software and data solutions that give hedge funds and financial services firms the visibility, speed, and confidence they need to make better decisions – faster.

Our platform delivers a unified source of truth that empowers our clients with real-time, actionable insights. We don’t just serve the industry – we help modernize it!

Siepe is profitable, privately held, and growing fast. We offer more than just competitive pay and great benefits—we offer the chance to do impactful work alongside sharp, driven teammates in a culture that rewards curiosity, initiative, and follow-through. Whether you come from finance, tech, or are charting a new path, you’ll find meaningful problems to solve, real ownership, and the momentum to grow your career with purpose.

Siepe is seeking a Senior Manager, SQL Development who owns the technical delivery of client-driven solutions from technical review and estimation through execution and release capable of building and scaling the Professional Services engineering function.

This role is ideal for someone who thrives in fast-moving, delivery-oriented environments, brings strong judgment to ambiguous problem spaces, and can turn complex, evolving client requirements into reliable, on-time execution. You will be accountable for how Professional Services work is scoped, designed, built, tested, and delivered—across custom reporting, data integrations, and data pipeline changes.

A core expectation: you will standardize how AI is used across the Professional Services organization—creating repeatable, safe, high-leverage AI workflows that increase throughput without sacrificing correctness, performance, or client trust.

Lead and mentor a team of engineers responsible for building custom, client-specific solutions; recruit and grow the team as Professional Services scales.

Own end-to-end technical delivery for Professional Services initiatives—from intake and feasibility review through development, validation, deployment, and post-release supportability.

Run technical review and estimation: validate feasibility, surface assumptions, identify dependencies, and produce credible schedules; establish “delivery contract” discipline (scope boundaries, acceptance criteria, change control).

Drive delivery accountability to commitments, timelines, and quality standards; proactively manage risk and communicate tradeoffs early.

Partner tightly with Support and Client Specialization to get work done: establish an engagement model (intake → triage → prioritization → delivery → release windows); define escalation paths, SLAs, and operational handoffs.

Build and oversee data-driven solutions—custom reports, exports, dashboards, performance/attribution reporting, and client-facing analytics.

Guide upstream data work when required (not “just reporting”): ingestion/landing adjustments, normalization, and curated reporting-ready outputs (data marts); vendor/custodian integration changes and schema drift handling.

Institutionalize testing and validation for client deliverables: automated regression testing for report outputs (golden datasets, contract/schema checks, tolerance-based comparisons); data quality tests for pipeline changes (nulls, duplicates, cardinality, anomaly thresholds); repeatable pre-release validation harnesses so client outputs don’t silently regress.

Standardize AI usage across Professional Services: create a PS “AI operating model” (prompt libraries, code review checklists, test generation patterns, estimation support); enforce human-in-the-loop controls for correctness, performance, and security; train engineers to use AI to accelerate spec-to-solution safely and consistently.

Participate in client discussions as needed to clarify technical requirements and delivery constraints, maintaining a delivery-first mindset rather than account ownership.

Background in financial services or regulated environments.

Experience partnering closely with Business Analysts and implementation teams.

Experience scaling or operating engineering delivery within a Professional Services model.

8+ years of software/data engineering experience, including leadership of delivery teams.

Prior experience in consulting or professional services environments with direct accountability for delivery outcomes.

Demonstrated ownership of estimation accuracy, scheduling, and delivery commitments.

Deep experience building data-centric solutions, reporting systems, exports, and client-facing analytics.

Strong SQL Server background and ability to lead high-stakes database work in production environments.

Report engineering at scale — deterministic export/report procedures with stable schemas and predictable performance.

Metadata-driven reporting patterns — dynamic pivots, configuration-driven layouts, and controlled client-specific variants.

Advanced analytical SQL — window-function–driven periodization and attribution-style computations.

Semi-structured + vendor-driven inputs — JSON handling and APPLY patterns to translate external schemas into normalized structures.

Reconciliation and correctness validation — drift detection and load validation patterns that prevent “silent wrong” outputs.

Performance engineering — plan-aware query design, indexing-minded implementations, and pragmatic approaches for parameter sensitivity.

Production-grade safety — structured failure signaling and guardrails for operationally safe reruns.

Practical experience applying AI tools in engineering workflows—and the maturity to standardize their use across a team: reusable prompts and scaffolding patterns, AI-assisted test case generation and validation routines, consistent PR review and “what changed / who is impacted” discipline.

Must have current and ongoing authorization to work in the country of employment without the need for visa sponsorship, now or in the future.