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# Staff Data Engineer, Core Migrations

Canonical URL: https://nextmove.md/fde/jobs/9726d76b0f5863ac

Machinify posts a staff FDE role to build what the customer runs in US, at $230,000–$260,000 base, above the staff+ FDE median of $225,000 across 388 postings with pay. Own client data migrations end to end, from reverse-engineering undocumented legacy systems through production deployment, reconciliation, and hypercare. Read from the employer’s posting on November 8, 2026.

- [Machinify](https://nextmove.md/fde/companies/machinify)

Posted Jun 30, 2026 by Machinify · open on Greenhouse as of Nov 8, 2026

**$230,000–$260,000** + equity US Remote

Own client data migrations end to end, from reverse-engineering undocumented legacy systems through production deployment, reconciliation, and hypercare.

- [See roles that fit me](https://nextmove.md/sign-up?from=%2Ffde%2Fjobs%2F9726d76b0f5863ac&placement=top)
- [View posting at Machinify](https://job-boards.greenhouse.io/machinifyinc/jobs/4303034009)

Free. Upload your resume once, see why each FDE role fits, and get introduced only when you say so.

## At a glance

### Posted base pay

$230K–$260K Above the median

Midpoint $245K · median $225K

This job $230K to $260K. Staff+ FDE postings, 388 postings: the middle 50% of posted pay is $197K to $262K, median $225K.

### The work

Builds what the customer runs

Balance **Mostly building**

Project stages

1. Pre-sales (not covered)
2. Proof of concept (not covered)
3. Implementation
4. Operations

- **Coding**: Writes production code

- **Builds for**: External customers

- **Level**: Staff+

- **Role**: Technical lead

### What they ask for

Experience

- **8+ years** Hands-on Data Engineer or Software Engineer experience

Background

- **Software engineering**
- **Implementation and data engineering**

### Do you meet what the posting states?

The posting asks for 8+ years. How many do you have?

The posting reads as a staff-level role. What level are you at now?

The work is remote from the US. Can you work from the US?

Which of these have you used in production?

Answer each one. Nothing is saved or sent.

[What postings ask for, by background →](https://nextmove.md/fde/paths)

## Conditions

- **Location**: US

- **Work arrangement**: Remote

- **Remote work restrictions**: Work from anywhere in the US

- **Pay**:

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## The job description from Machinify

Posted by Machinify on Jun 30, 2026

Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.

As a **Staff Data Engineer on the Migrations team**, you are the end-to-end technical and operational owner of client migrations. You will drive the full lifecycle, from deep-dive legacy analysis to production deployment, while orchestrating collaboration across Operations, Client Success, Product, Data Science and Platform Engineering. You don't just implement; you own the outcome.

This is a high-trust, high-autonomy role for someone who can think like an architect, execute like a senior engineer, and coordinate like a program manager — all on the same project. You'll own the problem space from discovery to go-live, making the defining architectural decisions and writing the code that brings them to life.

### What You’ll Do

- **Lead discovery & technical due diligence —** get to the bottom of poorly documented legacy systems (ETL, stored procedures, reporting layers, file feeds), reconstruct the business logic, and capture it in the lineage maps, mapping specs, and risk analyses everyone builds from.
- **Reverse-engineer complex legacy systems using agents— **you will be responsible for reverse-engineering complex, undocumented legacy systems (SSIS packages, stored procedures) where business logic is embedded, not documented. You must be able to reconstruct the intent of these systems to build modern, stable equivalents.
- **Drive ambiguity to resolution — **spot the unknowns early, own the open questions, and pull answers from clients, SMEs, and Operations instead of waiting to be unblocked.
- **Architect & build the migration pipelines** — turn intricate legacy logic into production-grade Airflow DAGs and Spark jobs on the Machinify platform, edge cases, payer-specific carve-outs, and business-rule exceptions included, owning the full flow from ingestion through reconciliation to steady-state handoff.
- **Make and document the hard architectural calls — **own the decisions that matter (pipeline design, partitioning strategy, validation approach) and leave a clear trail of the reasoning so others can learn from and build on it.
- **Prove correctness at scale — **build automated reconciliation frameworks that confirm, with confidence, that migrated output matches the source down to the row.
- **Own the program end to end — **be the single technical owner from kickoff through go-live and hypercare: scope, sequence, and track the work, surface risks before they bite, align Operations, Client Success, Platform Engineering, SMEs, and the client, and drive UAT through to sign-off.
- **Raise the bar for the practice** — Institutionalize migration knowledge by codifying runbooks and retrospectives, mentor L3/L4 engineers to build independent capability, and turn recurring migration pain points into scalable, reusable tooling.

### What You Bring

- **8+ years a**s a hands-on Data Engineer or Software Engineer, with **demonstrated experience independently owning complex, multi-stakeholder technical projects from start to finish**.
- **Strong Python and SQL** — fluent with complex, unfamiliar legacy code, not just greenfield work.
- **Apache Spark** — deep understanding of distributed processing, performance tuning, partitioning, and debugging at scale.
- **Apache Airflow** — advanced; comfortable designing and authoring production DAG architectures from scratch.
- **AI-assisted development** — actively uses coding agents (Claude, Copilot, Cursor, or equivalent) as a force multiplier in daily engineering work. Comfortable prompt-engineering for code generation, debugging, and documentation, and able to evaluate and trust AI output critically.
- **Legacy ETL ** **stack** — able to reconstruct intent from code and translate it faithfully into a modern stack (e.g., From SSIS, SQL Server stored procedures, T-SQL, or equivalent).
- **Data validation & reconciliation at scale** — experience designing automated frameworks that prove migrated data matches source systems with high confidence.
- **AWS** — proficient with S3, solid grasp of cloud-native data patterns such as partitioned object storage, secure cross-account access, and cost/performance trade-offs.
- **Cross-functional coordination** — proven ability to drive alignment across engineering, operations, and client-facing teams simultaneously, without losing velocity.
- **Clear technical communication** — able to write discovery specs, architecture docs, and stakeholder updates that are accurate, concise, and actionable for both technical and non-technical audiences.
- **Data-first mindset & fidelity — **a rigorous, data-first mindset, with deep experience in building automated reconciliation frameworks that guarantee 100% data fidelity between legacy and modern systems.

### 🌱 Why Join Us

- **Full ownership** — you own the whole arc of a migration, from first look to go-live. No fragmented handoffs — just the autonomy and context to do it well.
- **Immediate business impact** — every migration you land enables a health plan to process claims more accurately and efficiently.
- **Technical depth + breadth** — you'll work across legacy systems, modern orchestration, distributed compute, cloud infra, and client-facing delivery in every project.
- **Pivotal moment** — we're scaling the migrations capability for a fast-growing platform; the standards and patterns you set will shape how dozens of future migrations run

### What We Offer

- Work from anywhere in the US! Machinify is digital-first.

- Full Medical/Dental/Vision for employees & their families

- Flexible and trusting environment where you’ll feel empowered to do your best work

- Unlimited FTO

- Competitive salary, equity, 401(k) including employer match

The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. The base salary range for this role is $230k-$260k. We are hiring for different levels, and our Recruiting team will let you know if you qualify for a different role/range. Salary is one component of the total compensation package, which includes meaningful equity, excellent healthcare, flexible time off, and other benefits and perks.

### Equal Employment Opportunity at Machinify

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at: https://www.machinify.com/candidate-privacy-notice/

[View posting at Machinify](https://job-boards.greenhouse.io/machinifyinc/jobs/4303034009)

## About Machinify

AI-enabled healthcare payment integrity platform helping health plans prevent, detect, and recover claim payment errors across the payment lifecycle.

Late-stage private · 2000–5000 people

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