Cypress HCM

Compensation

Full Description

Senior Engineering Manager We’re looking for a strong data leader to build and scale our data function in a high-growth environment. You will lead data engineering, analytics engineering, and automation initiatives; owning everything from high-scale ingestion pipelines to AI agents that streamline workflows. This role is ideal for someone who thrives in early-stage (Series A–C) fintech or hedge fund environments and wants to have direct impact on business outcomes. What You’ll Do Data Platform & Pipelines • Own all ETL/ELT from external marketplaces and partners (listings, sold history, and transaction data). • Deliver broad coverage, freshness, and low-latency pipelines across APIs, feeds, and compliant web scraping. • Contribute to AI-driven detection, entity resolution, and robust outlier cleansing. • Set measurable SLOs for freshness, latency, and accuracy; implement monitoring, alerting, and runbooks. • Manage and expand the internal asset catalog to grow proprietary datasets. Analytics Engineering • Lead the analytics engineering function, partnering closely with analysts. • Build a self-service metrics layer and executive dashboards covering GMV, liquidity, funnels, buyer/seller behavior, and ops SLAs. • Own the event taxonomy and product analytics in Amplitude. • Design and manage A/B experimentation frameworks. Automation & AI Agents • Identify high-leverage manual workflows (QA, price suggestions, dispute resolution, KYC, payout reconciliation). • Deliver AI agents and automation systems to reduce manual work and increase efficiency. • Partner with Product, Ops, Risk, and Finance to prioritize automation by ROI and impact. Leadership & Strategy • Lead and grow a multidisciplinary team spanning data engineering, analytics engineering, and automation/ML engineering. • Manage vendor relationships and budgets. • Translate business objectives into a clear roadmap with measurable quarterly outcomes. Tech Stack You’ll Work With • Data Warehouse/Lake: Snowflake, S3 • Orchestration & Streaming: Airflow, data streaming services • Ingestion: Airbyte, Fivetran, Scrapy, Playwright • Transformations & Quality: dbt, Great Expectations, Soda, data catalog • Search & Analytics: Typesense, Tableau, Metabase, Amplitude • Infra/DevOps: AWS, Terraform/IaC, GitHub Actions, Datadog • AI/Agents: OpenAI, Anthropic, Vertex AI, Langchain, Pydantic AI, embeddings, RAGs, evaluation/guardrails What You Bring • 8–12+ years in data engineering/analytics, with at least 4+ years in hands-on leadership roles (managing managers and cross-functional teams). • Proven track record of building and operating large-scale data ingestion pipelines across diverse sources with strong SLAs. • Experience leading analytics engineering functions—partnering with analysts on metric definitions, experimentation, and executive reporting. • Strong proficiency in Python and SQL, with the ability to perform code reviews and contribute to schema/model design. • Experience implementing LLMs/agent systems in production with measurable outcomes. • Background in fintech, hedge funds, or marketplaces (pricing, risk, payments strongly preferred). • Startup experience in high-growth environments (Series A–C) with prior success scaling teams. Compensation: • $185-$230k base salary + equity