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Senior Manager, SQL Development

Job in Dallas, Dallas County, Texas, 75215, USA
Listing for: Siepe
Full Time position
Listed on 2026-02-24
Job specializations:
  • IT/Tech
    Data Science Manager, Data Analyst
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

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.

What You’ll Be Doing
  • 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…
Position Requirements
10+ Years work experience
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