Senior Data Engineer

General Motors (GM)

Confirmed live yesterday High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Austin, TX
Salary: $125,000–$168,650 / yr
Employment: Full-time
Posted: 2 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $163k

This role $147k

$110k $213k

below market most similar roles pay here above market

This role pays less than 63% of similar roles. Most pay $126,800–$199,775 — the blue band above. At the midpoint, this role pays about $147k versus about $163k for comparable roles.

Based on 240 similar postings.

Employer

About General Motors (GM)

General Motors (GM) is a leading American multinational automotive corporation founded in 1908 and headquartered in Detroit, Michigan.

General Motors (GM) currently has 186 open roles on FindRole.

Listed pay typically runs $158,000–$245,000 across 63 roles with salary data.

Most-posted roles

View all roles at General Motors (GM)

At a glance

TL;DR · Senior Data Engineer

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The Senior Data Engineer joins the GM Energy Data Engineering team to design, implement, and optimize scalable cloud-based data warehouse solutions. This role focuses on building an Operational Data Store to serve as a speed layer for advanced analytics and business intelligence. You will develop cloud data warehouse solutions using Databricks and Kubernetes, implement robust pipelines to ingest and process IoT data from diverse sources, and manage large-scale datasets using Apache Iceberg. Key responsibilities include optimizing data models, storage, and compute resources while ensuring data quality and security. Required technical skills include proficiency in SQL, Python, Java, and ETL tools, along with experience in Snowflake, Apache Flink, Spark, and cloud platforms like Microsoft Azure, AWS, or GCP. You will also utilize CI/CD practices and anomaly detection for monitoring.

What does a Data Engineer earn in Texas?

Median $168620 from 31 postings across 14 companies.

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Skills

Databricks Snowflake Apache Flink Python SQL Java Kubernetes Apache Iceberg Spark Kafka Spark Streaming Microsoft Azure AWS GCP CI/CD ETL IoT Data OCPP Protocol

What you'll do

Develop cloud data warehouse solutions using Databricks and Kubernetes.
Implement data pipelines to ingest and process IoT data from diverse sources.
Manage large-scale datasets using Apache Iceberg for scalable data lake operations.
Build an Operational Data Store (ODS) to serve as a speed layer for real-time use cases.
Optimize data models, storage, and compute resources for performance and cost efficiency.
Ensure data quality, security, and compliance across all cloud data platforms.
Set up monitoring tools and dashboards to track pipeline health and diagnose issues.

What we're looking for

Bachelor’s in software engineering, Computer Science, Information Technology, or a related field or equivalent experience.
7+ years experience designing, developing, and supporting enterprise applications.
Proven experience implementing cloud data warehouses using Databricks, Snowflake, or other data platforms.
Hands-on experience with Apache Flink or Spark for data lake pipelines.
Experience designing and building Operational Data Stores (ODS) as speed layers for analytic environments.
Experience with IoT data ingestion, processing, and analytics.
Strong proficiency in SQL, Python, Java, and ETL tools.
Proven cloud experience with at least one platform (Microsoft Azure preferred, AWS, or GCP).

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