Senior Data and BI Analyst / Developer
Orchid Software Solutions | Remote, Latin America | Full-time contract
About us
Orchid Software Solutions builds and operates software for healthcare and family-building services. Our products cover escrow for surrogacy and egg donation, agency management for fertility clinics, medical records retrieval, insurance risk management, and independent dispute resolution for healthcare payments under the federal No Surprises Act.
Our engineering team is distributed across the United States and Latin America. We work remotely and across time zones.
About the role
This is our first dedicated data and business intelligence role. You will own reporting end to end: the data architecture and modeling, define the metrics that drive decision-making, build the dashboards our operations teams rely on, and deliver the reporting our enterprise clients depend on.
You will start with our healthcare payments dispute resolution product, which has the largest data footprint and the most immediate reporting need. Once that reporting is running, the role expands across our other products, bringing one set of definitions to metrics that are currently produced product by product.
The interesting part of this job is not the dashboards, but what sits behind them. Much of what our applications display is calculated at read time by application code rather than stored directly in a column, which means the same business question can sometimes produce different answers depending on how it is calculated.
Your job is to define what each metric means, document those definitions, validate that they reconcile to the systems of record, and establish a trusted source of truth that both our teams and our clients can rely on. You'll also need to be comfortable explaining those definitions when different stakeholders ask for a different number.
If you enjoy bringing clarity to complex data and building reporting that people trust, you'll enjoy this role.
You will work alongside an engineering team of senior full-stack engineers and QA, a product manager, and business leadership in the United States. You will present the numbers directly to executives and to client counterparts, so this is a role for someone comfortable in front of an audience, not only in a query editor.
What you will do
- Build and maintain internal reporting for operational volume, case status and stage, cycle and resolution time, throughput, and service-level metrics.
- Own payment reconciliation reporting, where the tolerance for an approximate answer is zero.
- Design and ship scoped, self-service reporting for enterprise clients, so they can answer their own questions without going through our support team.
- Model data in our analytics warehouse: dimensional models, incremental transformations, and tested, documented pipelines.
- Own the metric layer. One definition per metric, the query that produces it, the business rule behind it, and a data dictionary anyone can read.
- Reconcile reporting against the source systems and keep it reconciled as the applications change.
- Work with role-scoped access and data minimization as a matter of routine. We handle regulated healthcare and payment data, and reporting is built to keep sensitive fields out of it.
- Improve data quality. Find the defects that make reporting wrong, quantify them, and drive the fixes with the engineering team.
- Turn ambiguous questions from executives and clients into defined metrics, and say so when a question cannot be answered from the data we hold.
- Extend the same patterns and definitions to our other products as the function grows.
What we are looking for
- Expert SQL. Complex analytical queries, window functions, and query performance work. You can tell the difference between a number that is surprising and a number that is wrong.
- Hands-on warehouse experience. ClickHouse, Snowflake, BigQuery, Redshift, or Databricks. You have modeled data in one, not only queried someone else's models.
- Dimensional and semantic modeling. You have built a reporting layer over a normalized transactional schema and owned the definitions that sat on top of it.
- Client-facing reporting, shipped. You have built reporting that external customers used, with the scoping and access controls that requires.
- You write code, not only queries. Production-quality work in Git, code review in both directions, and the ability to build and run your own transformation jobs.
- Stakeholder judgment. You can sit with an executive or a client, work out what they actually need, and push back when the ask does not hold up.
- Data governance in a regulated setting. Practical experience with role-based access, handling of personal or health data, and producing evidence for an audit. HIPAA, SOC 2, PCI, or similar.
- Clear written communication. Our team is distributed and most decisions happen in writing.
- Professional English, written and spoken. You will present to United States executives and to client counterparts. Fluency is required and is assessed in the first conversation.
Nice to have
- Healthcare payments, claims, or payer and provider data. Experience with No Surprises Act dispute resolution is a real advantage.
- Dbt or a comparable transformation framework, in production, with tests.
- Change data capture pipelines and the failure modes that come with them.
- Financial reconciliation reporting.
- Python for data work.
- Enough TypeScript to read an application and trace how a value is calculated.
- An embedded analytics or BI tool taken to production with external users, including row-level security.
- AWS, particularly RDS, S3, and IAM as it applies to data access.
What this role is not
- It is not a ticket queue for dashboard requests. You own definitions and you are expected to have opinions about them.
- It is not platform or infrastructure engineering. We have a platform team and you will partner with them.
- It is not machine learning or model development. That work sits with a separate team.
Tech you will work with
TypeScript and Next.js applications, MySQL and PostgreSQL as operational stores, ClickHouse as the analytics warehouse, change data capture between them, Python for data work, and AWS throughout. Our older products run on Python and Flask.
How we hire
- Introductory call with recruiting. Background, motivation, contract and rate expectations, availability, and time zone overlap. Conducted in English.
- Technical conversation with our CTO.
- Practical exercise. A realistic problem against an anonymized schema. Define a metric from an ambiguous business question, write the query, and tell us what in the data would make your answer wrong. We care as much about the second part as the first.
- Conversation with business leadership. How you handle a reporting request, and how you say no well.
- Conversation with the engineering team you will work with day to day.
Engagement and compensation
- Full-time independent contractor engagement.
- Fully remote.
- Unlimited PTO
