You’ll be working with novel, never-before-seen data: high-frequency mechanical, acoustic, electrical, and environmental signals from tens of thousands of power-constrained edge devices with intermittent connectivity, where ground truth comes from line crews in the field rather than a labeling vendor. This role will define new data problems that can be solved and change what the rest of the organization believes is possible with Gridware data.
Responsibilities
- Own the data platform end to end: ingestion, transformation, raw and sanitized data layers, and overall data architecture.Drive data quality, observability, lineage, and governance across the organization.
- Advance legacy migrations and step-change improvements to data platforms without disrupting the teams already depending on them.Applied data scienceManage a small, cross-functional data science team focused on rapid assessment of new data problems to determine valuable investments.
- Set the bar for rigor on early-stage analysis. Turn ambiguous questions into scoped, decision-ready answers for stakeholders across the company.Enablement and adoptionOwn the tooling, patterns, and support that let business domains build and maintain their own analytics and reporting under a federated ownership model.
- Build the data foundations that machine learning and applied research depend on.Drive analytics enablement for both technical and non-technical teams across the company.Org building
- Hire and design the data organization as it grows over the next year.Build and grow a world-class team of data engineering leaders.
- Balance incubation work against platform goals, and grow both sides of the org as the business scales
Required Skills
- Hands-on experience with modern lakehouse and streaming tooling (e.g., Databricks, Kafka, Kinesis, CDC pipelines, Airflow, Terraform) and able to contribute heavily to an architecture review with the team.Background in high-volume, machine-generated data: telemetry, sensor, IoT, observability, or logs, rather than primarily transactional or clickstream data.
- Experience running a data platform with real internal business stakeholders beyond engineering.Experience operating in a federated or domain-ownership model, with a clear point of view on what worked and what didn't.
- Experience building or substantially rebuilding platform capability, not only maintaining a mature platform.
Bonus Skills
- Background in physical-world or safety-critical systems: energy, IoT, robotics, autonomy, or aerospace.Experience with edge/cloud architecture under power or bandwidth constraints.
- Experience migrating an organization off a fragmented legacy state while it stayed live.Experience scaling with a company through a period of significant growth.