Senior Data Platform Engineer
$180k - $200kHarnham
Inspiren - Senior Data Platform Engineer
1. Role Overview
7. Technical / Functional Requirements Must-Haves
Key Traits / Soft Skills
13. Additional Notes / Nuances Need someone who can both build and influence . This should not be a passive ticket-taker. Strong preference for candidates who proactively create standards, tooling, and scalable systems.
1. Role Overview
- Title: Senior Data Platform Engineer
- Department / Function: Engineering / Data Platform / Infrastructure
- Reports To (Name / Title): Likely Engineering Leadership / Head of Data / Platform Lead / Aaron (Hiring Manager)
- Level (IC / Manager / Director / Exec): Senior IC
- Reason for Hire (Growth / Backfill / Transformation): Growth + Platform Transformation
- Urgency / Timeline: High priority / active immediate search
- Base Salary Range: $180,000 - $200,000
- Bonus (Structure / Target %): Likely discretionary / not primary lever
- Equity (Yes/No + Details): Yes, meaningful startup equity likely included
- Total Comp Range (if applicable): $200k+ depending on equity and experience
- Flexibility on Comp: Moderate to strong for top-tier talent
- Primary Location: Remote (US or Canada), NYC preferred
- Remote / Hybrid / Onsite (Days / Expectations): Fully remote with preference for proximity to NYC leadership hub
- Time Zone Requirements: EST or overlap strongly preferred
- Travel Requirements: Minimal occasional team offsites likely
- Relocation Offered (Yes/No): Likely case-by-case
- Visa Sponsorship (Yes/No): Unknown / likely limited
- Company Overview (Product, Mission, Market):
Inspiren builds AI-powered technology for senior living communities. Their platform blends real-time monitoring, analytics, workflow intelligence, and operational tools to improve resident outcomes, caregiver efficiency, and profitability. - Organizational Focus: AI, Data Infrastructure, Computer Vision, Healthcare Operations, Platform Scale
- Funding Stage / Revenue / Growth:
Series B growth-stage company with ~$155M total funding and strong recent momentum. - Team Size & Structure:
Scaling engineering org with growing investments across data, ML, CV, and software engineering. - Cross-Functional Partners:
Engineering, Product, Analytics, ML, Data Science, Operations, Leadership - Team Culture & Working Style:
Fast-paced, mission-driven, high ownership, builder mentality, collaborative, pragmatic
- Core Problem This Role Solves:
Build and scale the foundational data platform that powers analytics, ML systems, internal reporting, operational intelligence, and product decision-making. - Why This Role Matters Now:
Company growth is accelerating and data has become mission critical. Need mature infrastructure to support scale, reliability, and AI expansion. - What Success Looks Like (6-12 months):
- Streaming ingestion layer modernized
- Databricks environment optimized for scale/cost
- Governance and RBAC strengthened
- Reusable tooling adopted by internal teams
- Reliable platform trusted across business units
- Databricks platform architecture
- AWS data infrastructure
- Streaming ingestion (Kafka / Kinesis)
- Governance / RBAC / lineage
- Cost optimization
- Internal data tooling
- Build pipelines and platform components
- Optimize compute/storage spend
- Partner with ML / analytics stakeholders
- Troubleshoot reliability issues
- Improve observability and standards
- Assess current platform bottlenecks
- Improve ingestion reliability
- Implement quality frameworks
- Tighten governance model
- Multi-year scalable data platform roadmap
- ML / AI data enablement
- Self-service analytics infrastructure
- Best-in-class internal developer experience
7. Technical / Functional Requirements Must-Haves
- Strong Databricks hands-on experience
- Modern lakehouse / warehouse expertise
- AWS cloud experience
- Pipeline architecture at scale
- Governance / RBAC understanding
- Strong Python / SQL
- Strong communication skills
- Kafka / Kinesis
- Startup experience
- Healthtech experience
- AI tooling adoption (Cursor / Claude Code)
- Languages: Python, SQL
- Frameworks: Spark / PySpark
- Cloud / Infra: AWS, Databricks
- Tools / Platforms: Kafka, Kinesis, Airflow, Terraform, monitoring stack
- Years of Experience: 5-10+ years
- Target Background:
High-growth startups, healthcare tech, modern SaaS, data-heavy product companies, elite enterprise platform teams - Education Preferences: Strong technical foundation; degree helpful not mandatory
- Databricks ownership
- AWS production scale
- Streaming ingestion systems
- Governance / Unity Catalog / RBAC
- Cost optimization + stakeholder impact
Key Traits / Soft Skills
- Ownership mentality
- Strong communicator
- Builder mindset
- Comfortable in ambiguity
- Pragmatic operator
- Cross-functional collaborator
- Pure BI / reporting profile
- No Databricks hands-on depth
- No production scale systems
- Weak communication
- Highly siloed enterprise-only mindset
- No ownership examples
- Number of Stages: Likely 4-5
- Interview Format: Recruiter screen, HM screen, technical deep dive, stakeholder rounds, final
- Key Stakeholders Involved: Cameron, Aaron, Engineering leaders, cross-functional peers
- Timeline: Fast-moving if strong candidate identified
- Databricks depth
- Platform architecture
- Problem solving
- Communication
- Ownership / initiative
- Startup adaptability
- Technical depth
- System design
- Communication
- Leadership / ownership
- Business thinking
- Reliability mindset
- Cannot operate autonomously
- No hands-on architecture depth
- Weak stakeholder presence
- Overly theoretical profile
- Healthtech experience
- AI/ML platform support experience
- Elite company pedigree
- Strong cost optimization track record
- Mission-driven work improving elder care
- Real-world AI impact
- Strong funding and runway
- High ownership role
- Databricks + AWS modern stack
- Ability to shape platform strategy early
- Equity upside
- Meaningful technical challenges
13. Additional Notes / Nuances Need someone who can both build and influence . This should not be a passive ticket-taker. Strong preference for candidates who proactively create standards, tooling, and scalable systems.
Vacancy posted 4 days ago
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