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Location
Hybrid (Hyderabad, India)
Seniority
Senior · 5+ years exp
Visa
Sponsors visas in United States; no register of this country names it
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 6, 2026. First seen by Alion on Nov 6, 2026.

Overview
Company
Impact
Profile match
BusPatrol is a school bus safety technology company operating in North America. It equips school buses with camera systems, artificial intelligence and connected devices that detect and record vehicles illegally passing stopped buses, and runs stop-arm enforcement programs in partnership with school districts and local governments. The company is headquartered in Austin, Texas, United States.

Location: Remote

Travel: Less than 5%

Manages Others: No

Education: Bachelor’s Degree in a technical field

Experience: 5+ years of relevant experience in data engineering, 5+ years of SQL, 4+ years of Python, 4+ years of experience with schema design and dimensional data modeling

The Opportunity

The Data Engineer at BusPatrol will be responsible for building and maintaining our data infrastructure to support reporting, analytics, and data science initiatives. The ideal candidate will have strong skills in data architecture, ETL, SQL, and Python within a Git-managed environment, as well as a proven ability to collaborate with both business stakeholders and data team colleagues to deliver robust, scalable data frameworks. This individual will possess strong operational skills to drive efficiency and speed, expertise in building repeatable data engineering processes, strong project management abilities, and a forward-looking vision for delivering impactful data products. The candidate will responsibly leverage AI to accelerate development, maintaining full ownership of all outputs while mastering the codebase to ensure clean architecture and prevent software bloat.

Responsibilities:

· Create and orchestrate data pipelines within a state-of-the-art AWS environment (Redshift, EC2, EMR/Spark, S3, Lambda, Glue, etc.).

· Manage all aspects of the data and analytics ecosystem-from ingestion to ETL to aggregate tables-to meet analytics and reporting needs.

· Design and implement internal data pipeline processes and improvements using modern techniques such as automation, optimization, and infrastructure redesign for scalability.

· Develop scripts for scheduling data ingestion and synchronization and implement backend logic to create data marts based on business requirements for stakeholder self-service.

· Partner with data architects to build frameworks for defining metrics as code and optimizing data search and retrieval.

· Troubleshoot production data jobs and processes to resolve data quality issues and improve pipeline performance.

· Build and assemble large, complex data sets with multi-dimensional relationships to meet functional and non-functional business requirements.

· Develop integrations between systems to ensure seamless data flow.

Qualifications:

· Bachelor’s degree or higher in a quantitative or technical field (e.g., Computer Science, Statistics, Engineering) or equivalent experience.

· 5+ years of experience in data engineering, database engineering, business intelligence, or business analytics.

· 5+ years of SQL experience for reporting and transformation (Redshift, MySQL, PostgreSQL, Snowflake, Databricks).

· 4+ years of Python experience, including class development, within a Git-managed CI/CD team development environment.

· 4+ years of experience with schema design and dimensional data modeling.

· Strong interest in understanding business strategy, not just data architecture, and a focus on how data engineering contributes to organizational goals.

· Experience with Data Lake architectures and integrating structured and unstructured data into unified models.

· Ability to define and align to a long-term vision, with a focus on reliability, curiosity, and self-sufficiency in diagnosing issues by digging into code, data, and logs.

· Experience with API design and development of RESTful web services.

· Analytical mindset with the ability to structure and process qualitative data and draw insightful conclusions.

· Experience with data science and machine learning (a plus).

· Experience with GIS (a plus).

· Data visualization experience with tools such as Tableau (a plus).

· Experience with JIRA (preferred).

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