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Urban Sdk

Data Engineer

  • Seen live on Urban Sdk's site today
  • Mid level
  • Remote
Pay
Not stated
Location
Remote (United States)
Open for
12+ days
First seen
Oct 23, 2026

Posting record

No flags

Open 12+ days

The posting's record, oldest first
  1. Urban Sdk's site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Urban Sdk, so its true age is longer.

Last checked Nov 4, 2026.

How well do you match?

See how much of this posting your resume shows, and what it's missing.

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What it asks of you

3+ years of experience
“3+ years of experience as a data engineer or in a similar role.” (quoted from the posting)
Bachelor's degree asked for
“Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.” (quoted from the posting)

What the posting discloses

Not stated: Pay, real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Some employers add pay only on their own site. Check the original posting before you rule it out.

Skills mentioned

About the role

About Urban SDK

Urban SDK is shaping the Future of Smart Cities. We are pioneers in geospatial AI technology, providing public leaders with insights and automation for mission-critical decisions. We equip critical public services with geospatial AI, enabling precise, data-driven decisions with efficiency and confidence.

Our Commitment to People

We are committed to aligning business growth with professional outcomes for every employee. Our commitment has been recognized by Jacksonville Business Journal and Will Reed as a noted Best Places to Work.

About the role

We are looking for a skilled Data Engineer to design, build, and maintain scalable data pipelines and platforms that support our geospatial traffic analytics applications. The ideal candidate will have experience with Python, Databricks, S3, and modern data engineering practices, including automated testing, CI/CD, and data quality monitoring.

Responsibilities

  • Design, implement, and maintain scalable data pipelines and ETL/ELT workflows on Databricks and cloud platforms.
  • Manage large-scale geospatial and temporal datasets stored in AWS S3.
  • Collaborate with data scientists to productionize machine learning models and ensure smooth data availability.
  • Implement data validation, testing, and monitoring frameworks to ensure data accuracy, consistency, and reliability.
  • Optimize data storage and processing strategies to handle high volumes of traffic and mobility data efficiently.
  • Develop and maintain documentation for data workflows, architecture, and processes.
  • Work closely with cross-functional teams to understand data requirements and ensure timely delivery.
  • Stay up-to-date with the latest trends and best practices in data engineering, cloud technologies, and big data processing.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
  • 3+ years of experience as a data engineer or in a similar role.
  • Strong proficiency in Python and associated libraries for data engineering (pandas, PySpark, etc.).
  • Hands-on experience with Databricks and Spark for large-scale data processing.
  • Experience with AWS services, especially S3, and knowledge of cloud-based data architectures.
  • Solid understanding of data pipeline testing, version control, and CI/CD practices.
  • Experience with SQL and NoSQL databases.
  • Strong problem-solving skills and attention to detail.

Preferred Skills

  • Familiarity with geospatial data formats and processing (GeoJSON, Shapefiles, PostGIS).
  • Experience with workflow orchestration tools (Databricks, Prefect, or similar).
  • Knowledge of containerization (Docker/Kubernetes) and cloud-native data solutions.
  • Experience supporting machine learning pipelines in production.

Compensation

  • Location: Jacksonville, FL (Town Center Area) or Remote
  • Type: Full-time
  • Reports to: Director of Engineering
  • Salary Based on Experience
  • Annual Bonus
  • Medical, Vision, Dental, 401(k)
  • 21 Days Vacation
  • Office Lunch provided Daily

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