Note: The job is a remote job and is open to candidates in USA. TECHEAD is a leading national logistics and heavy equipment maintenance services provider, investing in a modern, cloud-native data platform. The Founding Data Engineer will be responsible for managing the cloud lakehouse architecture and ensuring data quality, while also collaborating closely with executive teams to drive business insights.
Responsibilities
- Manage, operate, and extend the modern cloud lakehouse architecture (Medallion architecture: Bronze, Silver, Gold layers; PySpark; Delta lake), including data pipelines, orchestration, monitoring, and performance tuning
- Build and maintain scalable ingestion feeds from core business systems, including cloud ERPs, payroll/HCM platforms, field service work-order platforms, equipment management tools, REST APIs, flat files, and SFTP endpoints
- Implement automated reconciliation routines, source-system tie-outs, and exception-reporting frameworks to ensure absolute trust in financial and operational metrics
- Develop and optimize semantic data models and executive dashboards in Power BI; collaborate with leadership on unified metric definitions and reporting logic
- Identify and deploy practical automation—including automated reporting, inter-system data syncs, and AI-assisted engineering and documentation workflows
- Oversee external data consultancies, contractors, and software vendors, maintaining tight control over deliverables, scope, and technical quality
- Maintain comprehensive data models, transformation logic, business dictionaries, and repeatable release/CI-CD processes
Skills
- Typically 6+ years of hands-on data engineering or analytics engineering experience. End-to-end platform ownership and active AI usage are weighted higher than raw years of tenure
- Advanced SQL and Python (PySpark experience strongly preferred), with proven experience building production pipelines on modern cloud data platforms
- Experience with cloud data platform technologies (Azure/Microsoft data ecosystems preferred; strong AWS or GCP backgrounds who can adapt quickly are highly welcomed)
- Deep expertise in dimensional modeling, star schemas, and warehouse/lakehouse design optimized for analytical workloads
- Hands-on experience developing semantic models, data sets, and optimized dashboard refresh routines in Power BI or similar enterprise BI tools
- Track record of integrating enterprise software suites (ERP, HRIS, CRM, and domain-specific operational platforms) within B2B contexts
- Active, hands-on integration of AI tools into daily workflows or technical solutions (candidates should be prepared to discuss concrete AI applications or automations built professionally or personally)
- Strong financial and operational acumen; comfortable speaking the language of executive leadership
- Thrives as an individual contributor in a growing environment; proactive, self-starting, and capable of prioritizing tasks without direct technical supervision
- Background in high-growth startups, boutique data consultancies, or mid-market environments where engineers own initiatives end-to-end
- Industry experience in logistics, transportation, supply chain, field services, equipment maintenance, or related operational sectors
- Track record of establishing formal data governance, engineering standards, and documentation in evolving tech environments
- Located in or open to the US Midwest / Great Lakes region (a plus, but not required)
Company Overview