🚀 Tech Lead, Data & Intelligence
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AI Summary
Lead the founding data and intelligence team by designing the platform architecture and establishing data culture. Own the end-to-end delivery of the data roadmap, ensuring high quality dbt models and reliable pipelines.
✨ About the Role
Equiem is a global PropTech company that has spent 14 years building a platform that transforms how people experience buildings. In that time, we've accumulated something remarkable: 7 years of rich behavioural event data from buildings across three continents — every tenant check-in, booking, event RSVP, access swipe, and login flowing through our platform is captured by Cortex, our central metrics service.
Until now, that data has been underutilised. Engineering has operated as a "human API" — fielding manual export requests from Customer Success, Support, and Product teams who can't self-serve. Business logic has been buried in QuickSight, invisible to engineers and inconsistent across reports. Ad-hoc queries have gone through a single person. That's changing.
We're forming a dedicated data & intelligence team for the first time, and this is the founding leadership position. You'll be building something genuinely new a team, an architecture, and a data culture on top of a solid foundation: a serverless AWS pipeline, a dbt transformation layer, and evolving BI tools.
As Tech Lead of the data & intelligence team, you'll sit at the intersection of technical architecture and team leadership. You'll shape how the data platform evolves, own its quality and reliability, grow the engineers around you, and be the bridge between data and the broader business.
🎯 What You'll Do
Essential:
• Strong hands-on data engineering background you've built and operated production ELT/ETL pipelines
• Deep dbt experience you know staging, intermediate, and mart models and have strong opinions on data modelling
• Solid familiarity with AWS data services: Athena, S3, Glue, Lambda, Kinesis, and/or Redshift
• Proven track record of technical leadership writing RFCs, leading architectural decisions, helping teams execute
• Demonstrated ability to mentor and grow engineers with examples of measurably improved capability
• Strong SQL skills write complex analytical queries, diagnose slow queries, design efficient mart tables
• Excellent communication translate data model decisions and pipeline tradeoffs for Product and CS teams
• Comfort with greenfield and emergent architecture
🛠️ Our Data Stack
• Experience building or owning a BI platform end-to-end not just transformation but tooling layers too
• Familiarity with event-driven data pipelines and streaming architectures (Kinesis, Kafka)
• Experience with customer-facing data products APIs, scheduled feeds, data integration
• Exposure to AI/ML data requirements
• Experience managing third-party delivery partners on data platforms
• Background in B2B SaaS, PropTech, or event-heavy platform businesses
• Exposure to compliance frameworks (SOC2, PCI DSS, GDPR)
💚 Why You'll Love It Here
Equiem is a global PropTech company that has spent 14 years building a platform that transforms how people experience buildings. In that time, we've accumulated something remarkable: 7 years of rich behavioural event data from buildings across three continents — every tenant check-in, booking, event RSVP, access swipe, and login flowing through our platform is captured by Cortex, our central metrics service.
Until now, that data has been underutilised. Engineering has operated as a "human API" — fielding manual export requests from Customer Success, Support, and Product teams who can't self-serve. Business logic has been buried in QuickSight, invisible to engineers and inconsistent across reports. Ad-hoc queries have gone through a single person. That's changing.
We're forming a dedicated data & intelligence team for the first time, and this is the founding leadership position. You'll be building something genuinely new a team, an architecture, and a data culture on top of a solid foundation: a serverless AWS pipeline, a dbt transformation layer, and evolving BI tools.
As Tech Lead of the data & intelligence team, you'll sit at the intersection of technical architecture and team leadership. You'll shape how the data platform evolves, own its quality and reliability, grow the engineers around you, and be the bridge between data and the broader business.
🎯 What You'll Do
- Own and evolve the data platform architecture making principled decisions about the data platform shape, shared data model, and pipeline patterns.
- Lead technical design for the team writing RFCs, ADRs, facilitating architecture discussions.
- Hold the standard for dbt model quality: staging → intermediate → mart discipline with meaningful tests and clear documentation.
- Identify and address non-functional requirements data freshness SLAs, reliability, PII handling, cost optimization.
- Provide technical mentorship to data engineers at all levels through design reviews, PR feedback, and pairing.
- Drive end-to-end delivery of the data team's roadmap from requirements through production-quality models and pipelines.
- Be the primary technical partner for Product, Customer Success, and Support on all data matters.
Essential:
• Strong hands-on data engineering background you've built and operated production ELT/ETL pipelines
• Deep dbt experience you know staging, intermediate, and mart models and have strong opinions on data modelling
• Solid familiarity with AWS data services: Athena, S3, Glue, Lambda, Kinesis, and/or Redshift
• Proven track record of technical leadership writing RFCs, leading architectural decisions, helping teams execute
• Demonstrated ability to mentor and grow engineers with examples of measurably improved capability
• Strong SQL skills write complex analytical queries, diagnose slow queries, design efficient mart tables
• Excellent communication translate data model decisions and pipeline tradeoffs for Product and CS teams
• Comfort with greenfield and emergent architecture
🛠️ Our Data Stack
- Event Ingestion: Cortex API Gateway → Kinesis Data Streams (168h retention) → Lambda → S3 (NDJSON, partitioned by date/hour).
- Storage: Amazon S3 raw NDJSON and consolidated Parquet (via Glue daily consolidation job), AWS Glue Crawler + Data Catalog.
- Transformation: dbt on Athena (dbt-athena-community adapter), staging → intermediate → mart layer structure, sqlfmt enforced.
- Query Engine: Amazon Athena serverless, pay-per-scan, Parquet + partitioning for cost management.
- BI & Visualisation: Metabase (ECS-hosted, RDS backend, Google OAuth, Athena + Redshift connections), QuickSight being phased out.
- Real-time / Search: AWS OpenSearch (Sigv4 auth, KMS encryption) powers segmentation and real-time queries.
- Data Exports: Client-specific Lambda exporters, scheduled SFTP exports, Bulk Export API (in progress).
- Infrastructure as Code: AWS CDK (TypeScript) 9 Cortex stacks.
- Emerging: Data Warehouse v2, RDS operational data integration (ZeroETL), GenAI analytics interface.
• Experience building or owning a BI platform end-to-end not just transformation but tooling layers too
• Familiarity with event-driven data pipelines and streaming architectures (Kinesis, Kafka)
• Experience with customer-facing data products APIs, scheduled feeds, data integration
• Exposure to AI/ML data requirements
• Experience managing third-party delivery partners on data platforms
• Background in B2B SaaS, PropTech, or event-heavy platform businesses
• Exposure to compliance frameworks (SOC2, PCI DSS, GDPR)
💚 Why You'll Love It Here
- You're building something new the data team doesn't exist yet, and you'll shape its culture and architecture from the ground up
- 7 years of rich event data captured by Cortex enormous analytical potential waiting to be unlocked
- An architecture you'll designData Warehouse v2 is in flight but the shape is yours to own
- Data that will drive AI the shared data model you build will underpin Equiem's AI capabilities
- Clear career progression to Principal/Staff Engineer or Head of Engineering
- Flexible remote working, wellbeing leave, paid parental leave, EAP, leadership development, great culture
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