General Motors · 3 days ago

Senior Data Engineer

Mountain View, CA

Full-time

Hybrid

Senior Level

$93K/yr - $149K/yr

5+ years exp

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Responsibilities

Design, construct, install, and maintain data architectures, including database and large-scale processing systems.

Develop and maintain ETL (Extract, Transform, Load) processes to collect, cleanse, and transform data from various sources inclusive of cloud.

Design and implement data pipelines to collect, process, and transfer data from various sources to storage systems (data warehouses, data lakes, etc.

Implement security measures to protect sensitive data and ensure compliance with data privacy regulations.

Build data solutions that ensure data quality, integrity, and security through data validation, monitoring, and compliance with data governance policies

Administer and optimize databases for performance and scalability

Maintain Master Data, Metadata, Data Management Repositories, Logical Data Models, and Data Standards

Troubleshoot and resolve data-related issues affecting data quality fidelity

Document data architectures, processes, and best practices for knowledge sharing across the GM data engineering community

Participate in the evaluation and selection of data related tools and technologies.

Qualification

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Data EngineeringData PrivacyETL/ELTData ArchitectureData Quality AssurancePerformance OptimizationSource Code ManagementRelease ManagementOperationsProgrammingBig Data ProcessingAzureDatabricksSparkPythonSQLGitHubAgile DevelopmentProblem-SolvingAnalytical SkillsEffective CommunicationCollaborationCuriosityIndependenceProactivitySalesforceCustomer Event dataCloud Certification

Required

5+ years of hands-on experience delivering enterprise-scale data and analytics solutions using modern hybrid cloud technologies with a focus on data curation for Customer Experience data science modeling and reporting.

Strong problem-solving and analytical skills with practical experience analyzing and curating large scale customer event data products from disparate data sources including 1st party and 3rd party data and map type data with variable structure.

In-depth knowledge of industry-standard Data Engineering practices including data privacy & security, ETL/ELT, data architecture, data quality assurance, performance optimization, source code management, release management, and operations.

Expert programming skills in data and analytics platforms, big data processing frameworks and languages, and development tools including Azure (or similar), Databricks, Spark, Python, SQL, and GitHub.

Effective communication and people skills, with the ability to collaborate effectively with cross-functional technical teams and non-technical stakeholders.

Naturally curious with the ability to work independently and proactively.

Experience working in an Agile development environment.

Bachelor's degree (or equivalent work experience) in Computer Science, Data Science, or a related field. Master's degree is a plus.