Staff Engineer - Data Platform & Analytics (Hybrid)

General Motors; United States; Hybrid; USD 150,000 - 185,000; Full time

Job summary

General Motors seeks a Staff Engineer to lead data management efforts, maintain master data and data standards, and design scalable data pipelines. You will assemble large data sets to support key business metrics such as customer acquisition and operational efficiency, collaborating across teams.

The role requires strong experience in Python/Java/C++/Scala and proficiency with Hadoop, Spark, Kafka, SQL/NoSQL databases, and stream processing.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or related field with 5+ years in staff/engineering roles
• or Master's degree with 3+ years in staff/engineering roles
• 3+ years of experience with Python, Java, C++, and Scala
• 2+ years of experience with Big Data tools (Hadoop, Spark, Kafka) and SQL/NoSQL databases (Postgres, Cassandra) and stream processing (Storm, Spark-Streaming)

Responsibilities

• Communicate and maintain Master Data, Metadata, Data Management Repositories, and Data Standards
• Assemble large, complex data sets to meet business requirements and deliver actionable insights
• Identify and implement internal process improvements to automate processes and scale data delivery
• Build industrialized analytic datasets and delivery mechanisms that leverage the data pipeline for customer acquisition and operational metrics

Skills

Python

Java

C++

Scala

Education

Bachelor's degree in Computer Science or related field

Master's degree in Computer Science or related field

Tools

Hadoop

Spark

Kafka

Postgres

Cassandra

Storm

Spark-Streaming

Job description

General Motors seeks a Staff Engineer to lead data management efforts, maintain master data and data standards, and design scalable data pipelines. You will assemble large data sets to support key business metrics such as customer acquisition and operational efficiency, collaborating across teams.

The role requires strong experience in Python/Java/C++/Scala and proficiency with Hadoop, Spark, Kafka, SQL/NoSQL databases, and stream processing.