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Senior Geospatial Data Engineer Jobs in Michigan

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Stellantis is looking for a Senior Data Engineer to join their AI & Data Analytics Team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that ...

Global Information Technology

Senior Data Engineer

Lansing, MI · On-site

$107K - $146K/yr

Senior Data EngineerJob Location: Lansing, MI (Hybrid)Job Type: Contract / Requirement:3-7 years of experience in Data Engineering, Business Intelligence, Data Analytics, or a related field.Strong ...

Kobie Marketing

Sr. Data Engineer

Detroit, MI · Remote

$104K - $142K/yr

As a Senior Data Engineer, you will be a key technical contributor and operational owner within our data engineering function. You will bring deep Snowflake expertise and strong engineering instincts ...

Pwc

Data Engineer - Senior Associate

Detroit, MI · On-site

$77K - $202K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

Pwc

Data Engineer - Senior Associate

Grand Rapids, MI · On-site

$77K - $202K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

Stellantis

Data Engineer

Auburn Hills, MI

$108K - $130K/yr

The AI & Data Analytics Team is looking for a Senior Data Engineer to join our team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that process ...

Expeditors

Data Engineer III/Senior (Analytics)

Romulus, MI · On-site

$102K - $138K/yr

A Successful Data Engineer III / Senior Data Engineer: * Building enterprise analytics solutions using Microsoft Fabric, Databricks, SQL, Python, and Power BI. * Design and develop semantic models ...

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Senior Geospatial Data Engineer information

What are the key skills and qualifications needed to thrive as a senior geospatial data engineer?

To thrive as a Senior Geospatial Data Engineer, you need advanced expertise in geospatial analysis, spatial databases, and programming languages like Python or SQL, often backed by a degree in GIS, computer science, or related fields. Familiarity with GIS platforms (such as ArcGIS or QGIS), cloud computing services, and big data frameworks is typically required, along with relevant certifications in GIS or cloud technologies. Strong problem-solving, communication, and project leadership skills set top performers apart in this role. These competencies are essential for designing and implementing scalable geospatial solutions that accurately support decision-making and organizational goals.

What is the difference between Senior Geospatial Data Engineer vs Geospatial Data Analyst?

AspectSenior Geospatial Data EngineerGeospatial Data Analyst
CredentialsBachelor's or Master's in GIS, Computer Science, or related field; experience with GIS software and programmingBachelor's or Master's in Geography, GIS, or related field; proficiency in GIS tools and data analysis
Work EnvironmentData engineering teams, GIS departments, tech companies, government agenciesResearch teams, GIS departments, consulting firms, government agencies
Employer & Industry UsageTech firms, environmental agencies, urban planning, transportationResearch institutions, government agencies, consulting firms

The Senior Geospatial Data Engineer focuses on building and maintaining geospatial data infrastructure, pipelines, and systems, often requiring programming and data engineering skills. In contrast, the Geospatial Data Analyst primarily interprets and visualizes geospatial data to support decision-making. Both roles require GIS knowledge but differ in technical depth and focus areas.

What are some typical challenges a senior geospatial data engineer faces when integrating diverse data sources?

One common challenge is ensuring data compatibility and consistency across various formats, such as raster, vector, and tabular data, which often originate from different providers or systems. Senior Geospatial Data Engineers must address issues like differing coordinate reference systems, data quality, and incomplete metadata. Collaborating closely with data scientists, GIS analysts, and software developers is crucial to develop robust pipelines and resolve integration issues efficiently. Staying updated with evolving geospatial technologies and standards also plays a key role in overcoming these challenges.

What is a senior geospatial data engineer?

A Senior Geospatial Data Engineer is a specialized data professional who designs, develops, and maintains systems that process and analyze spatial or geographic data. They work with large geospatial datasets, build data pipelines, and develop scalable solutions for mapping, location intelligence, and spatial analytics. These engineers often collaborate with data scientists, GIS specialists, and software developers to integrate geospatial data into applications and decision-making processes. Their expertise includes working with GIS software, spatial databases, and cloud-based geospatial tools. Senior-level engineers typically also mentor junior staff and help set technical direction for geospatial projects.
What are the most commonly searched types of Geospatial Data Engineer jobs in Michigan? The most popular types of Geospatial Data Engineer jobs in Michigan are:
What cities in Michigan are hiring for Senior Geospatial Data Engineer jobs? Cities in Michigan with the most Senior Geospatial Data Engineer job openings:
Senior Geospatial Data Engineer jobs near you

Data Engineer

Stellantis

Auburn Hills, MI • On-site

$108K - $130K/yr

Full-time

Re-posted 7 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

14th of 44 rated automakers

Job description

Job Summary:
Stellantis is looking for a Senior Data Engineer to join their AI & Data Analytics Team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that process massive datasets in both batch and real-time, ensuring scalable and reliable data architecture.
Responsibilities:
• Pipeline Development: Design and implement complex data processing pipelines using Apache Spark.
• Architectural Leadership: Build scalable, distributed systems that handle high-throughput data streams and large-scale batch processing.
• Infrastructure as Code: Manage and provision cloud infrastructure using Terraform.
• CI/CD & Automation: Streamline development workflows by implementing and maintaining GitHub Actions for automated testing and deployment.
• Code Quality: Uphold rigorous software engineering standards, including comprehensive unit/integration testing, code reviews, and maintainable documentation.
• Collaboration: Work closely with stakeholders to translate business requirements into technical specifications.
Qualifications:
Required:
• BA/BSc in Computer Science, Engineering, Mathematics, or a related technical discipline
• 5+ years of experience in the data engineering and software development life cycle.
• 4+ years of hands-on experience in building and maintaining production data applications, current experience in both relational and columnar data stores.
• 4+ years of hands-on experience working with AWS cloud services
• Comprehensive experience with one or more programming languages such as Python, Java, or Rust
• Comprehensive experience working with Big Data platforms (i.e., Spark, Google Big Query, Azure, AWS S3, etc.)
• Familiarity with time series database, data streaming applications, event driven architectures, Kafka, Flink, and more
• Experience with workflow management engines (i.e., Airflow, Luigi, Azure Data Factory, etc.)
• Experience with designing and implementing real-time pipelines
• Experience with data quality and validation
• Experience with API design
• Distributed Computing: Deep expertise in Apache Spark (Core, SQL, and Structured Streaming).
• Programming Mastery: Strong proficiency in Scala or Java. You should be comfortable building production-grade applications in a JVM-based environment.
• SQL Proficiency: Advanced knowledge of SQL for data transformation, analysis, and performance tuning.
• DevOps & Tools: Hands-on experience with Terraform for infrastructure management and GitHub Actions for CI/CD pipelines.
• Software Engineering Foundation: Solid understanding of data structures, algorithms, and design patterns. Experience applying 'Clean Code' principles to data engineering.
• Stream Processing: Experience with Apache Flink for low-latency stream processing.
• Scripting: Proficiency in Python for automation, data analysis, or scripting.
• Cloud Platforms: Experience with AWS, Azure, or GCP data services (e.g., EMR, Glue, Databricks).
• Data Modeling: Familiarity with dimensional modeling, Lakehouse architectures (Delta Lake, Iceberg), or NoSQL databases.
Preferred:
• Comprehensive knowledge of relational database concepts, including data architecture, operational data stores, Interface processes, multidimensional modeling, master data management, and data manipulation
• Expert knowledge and experience with custom ETL design, implementation and maintenance
• Comprehensive experience designing, implementing, and iterating data pipelines using Big Data technologies
• Certification in AWS or other cloud providers
• Experience with Databricks notebook workflows
• Experience with Terraform
Company:
Stellantis is an Franco-Italian-American automotive holding company that manufactures automobiles. Founded in 2021, the company is headquartered in Hoofddorp, NLD, with a team of 10001+ employees. The company is currently Late Stage.

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