Geospatial Data Engineer
As the first geospatial hire, you'll design and build data processing systems that enable autonomous flight decisions, directly impacting mission success in challenging conditions.
553 total jobs
102 new jobs this week
As the first geospatial hire, you'll design and build data processing systems that enable autonomous flight decisions, directly impacting mission success in challenging conditions.
Build scalable streaming and batch data pipelines, govern high-performance production databases, and advance secure, near-real-time data systems while ensuring dataset quality.
Design and build operational data systems at Keycard, focusing on pipelines, storage layers, and APIs for real-time enforcement and customer insights.
As a Data Engineer on the Growth team, you will build and scale data pipelines, ensure data quality, and empower teams with self-service data access.
As a Senior Data Engineer, you will lead data platform strategy, own the Snowflake data lake, and drive cross-functional initiatives to ensure trusted and scalable data for AI-driven underwriting.
As a Senior Data Engineer, you will own the daily ingestion engine, ensuring the reliability and scalability of data pipelines that process calendar data for over 14 million listings.
As a Backend AI & Data Pipeline Engineer, you will design and maintain scalable data processing infrastructures that enhance Yuzee's intelligent course and job matching platform.
The Data Engineer will build, maintain, and optimize data pipelines and infrastructure to support analytics and reporting, ensuring data quality and reliability.
Own complex data engineering initiatives by designing scalable architectures and reliable pipelines, optimizing Snowflake performance and cloud costs, and supporting analytics, marketing, machine learning, and AI applications.
Design and build scalable Snowflake and AWS data ingestion pipelines, validation frameworks, and governance components that deliver reliable, trusted data for analytics and business-critical workflows.
As a Senior Data Engineer, you will own and enhance data pipelines on GCP, ensuring high-quality data is available for analytics and machine learning across the organization.
As a Senior Database Reliability Engineer, you will design, build, and scale the database platform used across Sezzle's applications, ensuring reliability and performance.
As a Senior Database Reliability Engineer, you will design, build, and scale the database platform for Sezzle's applications, ensuring reliability, security, and scalability.
As a Senior Database Reliability Engineer, you will design, build, and scale the database platform, ensuring reliable and secure database usage across Sezzle's applications.
As a Senior Database Reliability Engineer, you will be responsible for improving how Sezzle applications connect to, migrate, operate, observe, and scale their databases.
As a Senior Database Reliability Engineer, you will design, build, and scale the database platform for Sezzle's applications, ensuring reliability, security, and scalability.
Designs and scales shared database platform components, tooling, and standards, improving reliability, security, performance, and developer workflows across production database systems.
Design and build reliable data transformations and scalable big data systems, shaping engineering standards while taking data solutions from implementation and testing through production.
The Data Quality Engineer will ensure data quality and reliability by designing frameworks, implementing automated checks, and collaborating with teams to validate data pipelines.
Ensure data quality and reliability across Azure and Databricks platforms by testing pipelines, automating validation, reconciling source data, and partnering with engineering and business teams.
Build and maintain data quality frameworks and automated checks across Azure and Databricks pipelines, validating data from ingestion through reporting and resolving issues with engineering and business teams.
As a Data Engineer, you will design and implement scalable data platforms to support analytics and AI initiatives, ensuring data quality and compliance in financial services.
Break down engineering workflows into tool-usable steps, evaluate model responses against verified information, and label, proofread, and improve engineering-related outputs.
Design and implement large-scale data platforms and pipelines on Databricks, leading technical direction and supporting team growth in complex enterprise environments.
Those that list pay offer a median of $178,000 a year. The middle half pay between $141,000 and $205,000.
| Level | Range | Middle half ยท median |
|---|---|---|
| All levels | $141Kโ$205K ยท $178K |
22% of these listings post pay. From 54 listings with pay in USD, at most three per company.
6% of these listings are open worldwide and 2% to a whole region, like Europe or Latin America. The other 91% hire in specific countries:
From 431 listings that state where they hire.
What hiring companies here ask for far more often than across all remote jobs, so it is worth putting front and center on your resume.
Share of the 217 companies hiring here that ask for each skill, and how many times as often as across all remote jobs. Soft skills like communication are left out.
Half stop taking applications within 28 days of being posted, and 1 in 4 within 10 days. Applying in the first week counts.
10 days
1 in 4 closed by then
28 days
Half closed by then
57 days
3 in 4 closed by then
From 220 listings that closed in the last 120 days, at most three per company.