Senior Software Engineer: Cloud, Microservices & Big Data

Talentify; Dearborn (MI); Hybrid; USD 138,000 - 179,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vehicle discounts

Tuition assistance

Employee ERGs

Paid time off

Paid holidays

Job summary

Ford Motor Company in Dearborn, Michigan, seeks a Senior Software Engineer for a hybrid role combining remote work with on-site collaboration. You will develop a Test Data Management strategy using ASAM ODS and cloud technologies to support test data workflows.

Design cloud-based architectures for time-series data, implement ETL pipelines and microservices using Java, Spring Boot, Angular, SQL, and big data tools (Snowflake, Apache Spark) to extract business insights from large datasets.

Qualifications

• Bachelor’s degree or foreign equivalent in Computer Science Information Technology Management, Mechanical Engineering or a related field and 6 years of progressive, post-baccalaureate experience.
• 6 years of experience with Java full stack, REST APIs, and scalable web applications.

Responsibilities

• Develop Test Data Management strategy and platform leveraging ASAM ODS and cloud technologies.
• Design cloud-based software architecture for time-series data storage, indexing, aggregation, and retrieval using big data technologies.
• Implement data analysis and visualization capabilities for test data using ASAM ODS APIs, ETL pipelines, and cloud services.
• Architect microservices-based software solutions following Ford standards.

Skills

Java

REST APIs

SQL

ASAM ODS

Elastic Search

Angular

Spring Boot

Snowflake

Apache Spark

Education

Bachelor's degree in Computer Science / Information Technology or related field

Job description

Ford Motor Company in Dearborn, Michigan, seeks a Senior Software Engineer for a hybrid role combining remote work with on-site collaboration. You will develop a Test Data Management strategy using ASAM ODS and cloud technologies to support test data workflows.

Design cloud-based architectures for time-series data, implement ETL pipelines and microservices using Java, Spring Boot, Angular, SQL, and big data tools (Snowflake, Apache Spark) to extract business insights from large datasets.