Purpose-built for the ambulatory surgery center setting, Sigmatic automates manual workflows, provides real-time insights, and streamlines decision-making to reduce costs and maximize margins.…
Purpose-built for the ambulatory surgery center setting, Sigmatic automates manual workflows, provides real-time insights, and streamlines decision-making to reduce costs and maximize margins.…
Operational and financial inefficiencies in provider-owned healthcare centers—particularly ambulatory surgery centers.
Industry
Healthcare / Healthtech
Funding Track Record
Pre-Seed
Founders
What we do
Join the Team
Data Engineer
RemoteUS
Remote • US
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Company Overview
Sigmatic is building the operating system for ambulatory surgery centers (ASCs). We help healthcare operators gain real-time visibility into cost, utilization, and performance using modern data infrastructure, AI, and automation—without disrupting existing clinical workflows.
Our platform ingests and normalizes complex healthcare, financial, and operational data to drive better decisions for administrators, operators, and executives. Data is core to everything we do.
Role Overview
We are seeking a
Staff Analytics Engineer
to lead the technical direction of Sigmatic’s analytics and data platform. This is a
hands-on, high-ownership role
at the center of our engineering organization.
You will own the design, build, and evolution of our analytics foundation—from ingestion and modeling to governance and BI—powering insights used daily by our internal teams and healthcare customers. You’ll help move Sigmatic from early data pipelines to a
production-grade, scalable analytics platform
.
Our analytics stack is built on
Databricks, Delta Lake, Unity Catalog, PostgreSQL, and AWS
.
This role has direct impact on:
Product velocity
Customer onboarding and proof of value
Executive and operator decision-making
The long-term scalability of Sigmatic’s platform
What You’ll Do
What We’re Looking For
Why This Role at Sigmatic
You’ll shape the
data foundation
of a healthcare platform at a pivotal stage.
Your work will directly impact real healthcare operators—not just dashboards.
High ownership, low bureaucracy, and meaningful technical influence.
Opportunity to grow into a
principal-level technical leader
as the company scales.
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Lead the
architecture and engineering
of Sigmatic’s end-to-end analytics platform, including ingestion, transformation, modeling, and BI delivery.
Own and evolve
Databricks pipelines
, ensuring reliability, accuracy, performance, and cost efficiency.
Design and maintain
Delta Lake and Unity Catalog datasets
supporting operational, clinical, financial, and executive use cases.
Serve as the technical authority on
data architecture and modeling
, including schema design, table strategy, and governance best practices.
Build reusable, well-documented data models that support utilization metrics, financial reporting, and operational analytics.
Partner closely with
product, engineering, and business stakeholders
to translate requirements into scalable technical solutions.
Lead improvements in
data quality, observability, testing, and CI/CD
for analytics code and datasets.
Mentor engineers and analysts, raising the bar for analytics engineering practices across the team.
Implement and enforce
secure data practices
, ensuring compliance with HIPAA, HITRUST, and internal security standards.
Evaluate and introduce tools, frameworks, and processes that improve developer productivity and system reliability.
Contribute to hiring and technical interviews as we scale the data team.
Operate as a senior individual contributor with
high ownership, autonomy, and accountability
in a fast-moving startup environment.
Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.
Deep experience in
analytics engineering or data engineering
, including Spark, Databricks, Delta Lake, or similar large-scale systems.
Strong understanding of
AWS cloud architecture
, including compute, storage, networking, and identity.
Expertise in
data modeling, ETL/ELT design
, and building maintainable, production-grade data pipelines.
Experience with
BI tools (e.g., Power BI)
, including dataset modeling and performance optimization.
Solid grasp of modern data architecture patterns (batch vs. streaming, distributed systems, event-driven pipelines).
Strong knowledge of
data security and governance
, especially in regulated environments (HIPAA, HITRUST).
Ability to set technical direction, influence across teams, and operate as a senior technical leader.
Proven track record of delivering
reliable, business-critical data systems
in production.
