Lead Data Engineer

Regrid

Location: U.S.
Workplace: Remote
Employment: Full Time
Salary: USD 160,000–190,000/yr

Posted 2mo ago

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Responsibilities

Mentor and support a small team through technical leadership, coaching, and regular feedback.
Coordinate project priorities and team execution while remaining an active contributor to delivery.
Establish engineering standards and promote operational excellence.
Participate in hiring, onboarding, and career development efforts.
Foster a culture of ownership, accountability, and continuous learning.
Shape the long-term technical direction of the data platform.
Design and evolve scalable, cloud-native architectures supporting parcel, address, enrichment, and operational datasets.
Guide architectural decisions around storage, processing, orchestration, governance, and observability.
Conduct architectural reviews and establish best practices for reliability, maintainability, and scalability.
Partner closely with other departments and leadership teams to align technical investments with business goals.
Evaluate emerging technologies and recommend strategic improvements to the platform.
Build and operate AWS-native data platforms leveraging services such as S3, Glue, Athena, EMR, Lambda, Fargate, and related technologies.
Design, build, and maintain medallion-style data pipelines processing large-scale geospatial and property datasets.
Establish and monitor service-level objectives for data quality, freshness, reliability, and performance.
Contribute hands-on code and technical solutions alongside the engineering team.
Establish best practices around security, access controls, environment management, deployment automation, and disaster recovery.
Improve observability through logging, monitoring, alerting, and operational metrics.
Evaluate and implement emerging technologies.
Work closely with leadership on machine learning-powered enrichment initiatives.
Research new tools, frameworks, and methodologies that improve scalability, performance, and developer productivity.
Drive continuous improvement across data engineering processes and platform capabilities.

Requirements

6+ years of experience in data engineering or related technical disciplines.
A deep curiosity and vision for how data infrastructure can unlock new levels of geographic intelligence and product innovation.
Strong experience building distributed data pipelines and cloud-native data platforms.
Deep proficiency with Python and modern software engineering practices.
Experience with AWS-based data infrastructure.
Experience mentoring engineers and leading technical initiatives.
Strong communication and collaboration skills, with the ability to partner effectively across engineering, product, support, and executive leadership teams.
Experience working with large and complex datasets: Regrid maintains a spatial dataset of 160M parcel polygons, 180M address points, 180M building footprints, and more.
Experience with geospatial datasets, including points, polygons, spatial indexing, and spatial joins at scale, is highly valued.
Comfort working across file-based, table-based, and relational data systems.
Familiarity with modern data technologies such as GeoParquet, Apache Iceberg, Apache Sedona, GeoPandas, DuckDB, Arrow, Spark, and PostGIS.
Experience implementing Infrastructure as Code using Terraform and/or CloudFormation.
Exposure to machine learning pipelines, data enrichment workflows, or production ML infrastructure is a plus.

Skills

Python
AWS
S3
Glue
Athena
EMR
Lambda
Fargate
GeoParquet
Apache Iceberg
Apache Sedona
GeoPandas
DuckDB
Arrow
Spark
PostGIS
Terraform
CloudFormation

Responsibilities

Requirements

Skills

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