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Data Engineer II
GM FinancialCore Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and managing large-scale data systems using technologies such as Hadoop, Spark, and cloud platforms. Proficient in building ETL/data pipelines and ensuring data privacy and compliance with regulations like GDPR.
Highest-signal resume keywords
HadoopSparkETL/Data Pipeline DevelopmentAzureData Privacy Compliance
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Work with internal business partners to identify, capture, collect, and format data from external sources, internal systems, and the data warehouse
- Extract features of interest from collected data
- Contribute to evaluation, research, and experimentation with batch and streaming data engineering technologies
- Work with data engineering groups to showcase emerging technology capabilities and enable adoption of new technologies and techniques
- Coordinate with Privacy Compliance to ensure proper data collection and handling
- Create and implement business rules and functional enhancements for data schemas and processes
- Perform data load monitoring and resolution
- Work with internal business clients to solve data availability and activation issues
Requirements
What you’ll need- Experience designing, processing, and managing large-scale data using Hadoop, Spark, Kafka, HDFS, or similar distributed platforms
- Hands-on experience with Azure, AWS, or Google Cloud
- Experience with infrastructure-as-code tools such as Terraform, ARM Templates, or CloudFormation
- Experience building and maintaining ETL/data pipelines
- Experience working with JSON, Parquet, relational databases, cloud databases, and messaging platforms
- Understanding of data lakes, lakehouses, streaming pipelines, and object storage technologies such as ADLS Gen2 and Amazon S3
- Experience with SQL and NoSQL technologies such as Cosmos DB, MongoDB, Cassandra, or Redis
- Experience with Docker and Kubernetes
- Familiarity with Git, CI/CD, build tools, code quality tools, and artifact management
- Experience with Adobe Experience Platform, Real-Time CDP, Journey Analytics, tag management platforms, SDKs, and REST APIs
- Understanding of data privacy, security, governance, and regulatory considerations, including GDPR
- Experience working in Agile environments using Scrum, SAFe, or similar methodologies
- Strong problem-solving and troubleshooting skills
- Strong written and verbal communication skills
- Ability to use AI tools such as Microsoft Copilot
- Ability to evaluate AI outputs for accuracy, compliance, and bias
- Experience integrating AI into workflows
- Familiarity with AI-assisted research, summarization, and content generation
- Understanding of responsible AI use, including ethics and data protection
- 2-4 years of hands-on experience with data engineering required
- High School Diploma or equivalent required
- Bachelor’s Degree in a related field or equivalent experience required
- Must not require visa sponsorship now or in the future
Benefits
Comp & perks- 401K matching
- Bonding leave for new parents: 12 weeks, 100% paid
- Tuition assistance
- Training
- GM employee auto discount
- Community service pay
- Nine company holidays
- Competitive pay and bonus eligibility
- Flexible hybrid work environment
- Two days a week in office
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringSQLNoSQLJSONParquetDockerKubernetesTerraformAI IntegrationData Lake Understanding
Soft Skills
Problem-SolvingCommunication
Tools & Technologies
AWSGoogle CloudKafkaHDFSAdobe Experience PlatformREST APIsCI/CDGit
Certifications & Qualifications
Bachelor’s Degree
Industry Keywords
AgileGDPRData GovernanceStreaming PipelinesObject Storage