Principal Platform and Data Engineer role

Spectraforce Technologies, Inc.; Raleigh (NC); Hybrid; USD 180,000 - 240,000; Part time

Job summary

Spectraforce Technologies, Inc. is seeking a Principal Data & Platform Engineer - Player to own the architecture and lead the build of a modern data foundation.

The role combines hands‑on delivery with strategic oversight, guiding a Senior Data Engineer and ensuring security, reliability, and long‑term maintainability of the platform. You will architect and implement via Azure and Snowflake, automate environments, and establish DataOps practices to support multiple AI tools and models as the

Qualifications

• Experience standing up and operating a modern data platform as the senior technical lead for other engineers.
• Strong data and cloud fundamentals, with deep hands‑on experience in Azure and Snowflake or equivalent.
• Excellent automation instincts across infrastructure as code, CI/CD, orchestration, testing, observability, and DataOps.
• Experience integrating imperfect SaaS and enterprise data through APIs, files, events, or change‑data‑capture patterns, then turning it into coherent shared models.
• The ability to debug across cloud infrastructure, pipelines, data models, permissions, and production operations instead of handing problems between specialists.
• Pragmatic architecture judgment: durable day one, avoids rework and premature industrialization.
• High ownership and clear communication; turn ambiguity into decisions and raise risks early.

Responsibilities

• Own the target architecture and a sequenced delivery plan tied to the first high‑value data and AI use cases.
• Build the core Azure and Snowflake foundation using managed services where they reduce operating burden without creating lock‑in or complexity.
• Lead source integration and ingestion across firm systems, shaping data into trusted, reusable models for entities like companies, people, deals, relationships, documents, and portfolio information.
• Automate infrastructure, deployments, testing, monitoring, data‑quality checks, backfills, and recovery so routine operations don’t require manual intervention.
• Set the security and reliability baseline: least privilege, environment separation, secrets, auditability, data classification, lineage, backups, and clear production ownership.
• Lead and unblock the Senior Data Engineer through direct collaboration, design and code review, clear standards, and fast decisions.
• Work closely with AI, investment, and IT teams; document the platform and transfer enough context for the firm to operate and extend it.

Skills

Azure

Snowflake

DataOps

CI/CD

Automation

Cloud architecture

Security

Leadership

API/Data integration

Tools

CI/CD tooling

Job description

Principal Data & Platform Engineer - Player

6+ months

Boston,MA (Hybrid preffered/open to remlote for highly qualified candidates)

Position Summary:

Client is building the data foundation for a firm‑wide AI and analytics program. Our environment centers on Azure and Snowflake, with data coming from DealCloud, Raylu, Microsoft 365, market‑data products, portfolio systems, and other firm sources. The near‑term goal is straightforward: move the right data into a governed data lake and Snowflake, keep it current, and make it dependable for downstream use.

As Principal Data & Platform Engineer, you will own the architecture and lead the build. You will choose a practical set of managed Azure services, automate the environment, build the hardest integrations, and establish the DevOps and DataOps practices needed to run the platform with a small team.

This is a player‑coach role. You will remain deeply hands‑on while directing a Senior Data Engineer, reviewing critical work, and making the few decisions that shape security, reliability, and long‑term maintainability. We care more about judgment, ownership, and a record of shipping working platforms than familiarity with every product in our stack.

The platform will support multiple AI tools and models over time. Your job is to create clean, governed interfaces to data so the application layer can change without forcing the data foundation to be rebuilt.

What you will do

• Own the target architecture and a sequenced delivery plan tied to the first high‑value data and AI use cases.
• Build the core Azure and Snowflake foundation using managed services where they reduce operating burden without creating unnecessary lock‑in or complexity.
• Lead source integration and ingestion across firm systems, then shape the resulting data into trusted, reusable models for companies, people, deals, relationships, documents, and portfolio information.
• Automate infrastructure, deployments, testing, monitoring, data‑quality checks, backfills, and recovery so routine operations do not depend on manual intervention.
• Set the security and reliability baseline: least privilege, environment separation, secrets, auditability, data classification, lineage, backups, and clear production ownership.
• Lead and unblock the Senior Data Engineer through direct collaboration, design and code review, clear standards, and fast decisions.
• Work closely with Great Hill's AI, investment, and IT teams; document the platform and transfer enough context for the firm to operate and extend it.

What we are looking for

• A record of personally standing up and operating a modern data platform while serving as the senior technical lead for other engineers.
• Strong data and cloud fundamentals, with deep hands‑on experience in Azure and Snowflake or the ability to transfer comparable experience quickly.
• Excellent automation instincts across infrastructure as code, CI/CD, orchestration, testing, observability, and DataOps.
• Experience integrating imperfect SaaS and enterprise data through APIs, files, events, or change‑data‑capture patterns, then turning it into coherent shared models.
• The ability to debug across cloud infrastructure, pipelines, data models, permissions, and production operations instead of handing problems between specialists.
• Pragmatic architecture judgment: knows what must be durable on day one, what can wait, and how to avoid both shortcuts that create rework and premature industrialization.
• High ownership and clear communication. You can turn ambiguity into decisions, make progress visible, raise risks early, and leave the team stronger than you found it.

Preferred background

• Experience with sensitive financial, investment, or professional‑services data.
• Experience delivering an initial platform build with a small internal team or as a senior consulting lead.
• Experience simplifying a fragmented data environment through managed cloud services and disciplined automation.

What success looks like

Within the first 90 days, Client has an agreed architecture, automated Azure and Snowflake environments, and at least one priority source flowing through observable pipelines into trusted data models. The Senior Data Engineer is productive against clear standards, the AI team can use the data safely, and the operating model is simple enough for a small team to sustain.