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Senior Data Engineer
General Motors. Design, build, and optimize industrialized data assets and data pipelines supporting Business Intelligence and Advanced Analytics .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and optimizing data pipelines and assets, with proficiency in Fivetran, Azure, and Spark. Capable of leading data-driven solutions and mentoring teams while applying Agile methodologies and CI/CD principles.
Highest-signal resume keywords
Data Engineering ExperienceFivetran Pipeline DevelopmentAzure Data Platform ManagementSpark and Kubernetes ProficiencyETL Frameworks and Big Data Processing
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonScalaSQLETL FrameworksSparkKubernetesData StreamingDatabricksData NormalizationData Modeling
Soft Skills
CollaborationCommunicationLeadershipMentoringCoaching
Tools & Technologies
FivetranAzure Data Lake StorageEvent HubsAzure SQLKafkaHadoopHiveHBaseSnowflakeDelta Lake
Industry Keywords
Data GovernanceMetadata ManagementData QualityObservabilityMedallion Architecture
Tech Stack
Tools & technologiesApacheAWSAzureCloudETLGoogle Cloud PlatformHadoopHBaseKafkaKubernetesNoSQLPythonScalaSparkSQL
About the role
Key responsibilities & impact- Design, build, and optimize industrialized data assets and data pipelines supporting Business Intelligence and Advanced Analytics
- Assemble large, complex data sets meeting functional and non-functional business requirements
- Identify and implement process improvements, automation, data delivery optimization, and infrastructure redesign for scalability
- Lead and deliver data-driven solutions across multiple languages, tools, and technologies
- Develop and configure end-to-end Fivetran data pipelines for efficient ETL
- Connect APIs, SaaS platforms, and databases to Fivetran; manage schema mapping and transformations
- Monitor pipeline performance, troubleshoot issues, and improve scalability and reliability
- Contribute to architecture discussions, solution design, and strategic technology adoption
- Design and develop source-system integrations from files, database extracts, and APIs
- Deliver data solutions meeting SLA requirements
- Work with operations teams to resolve production platform issues
- Apply Agile, design thinking, and continuous deployment practices
- Develop tooling and automation for repeatable deployments and production monitoring
- Collaborate with business and technology partners, providing leadership, best practices, and coaching
- Mentor peers and junior engineers and educate colleagues on emerging technologies
- Support General Motors Manufacturing and partners with plant data solutions improving decisions, asset maintenance, safety, operational performance, and Vehicle Build Data
- Design and operationally manage a cloud-native Azure data platform
- Monitor and troubleshoot platform workloads; optimize Spark jobs, cluster configurations, and SQL warehouses
Requirements
What you’ll need- Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent experience
- 7+ years of data engineering/development experience, including Python or Scala, SQL, and relational/non-relational data storage
- Experience with ETL frameworks, big data processing, and NoSQL
- 3+ years of experience in distributed data processing with Spark and container orchestration with Kubernetes
- Proficiency in data streaming in Kubernetes and Kafka
- Proven experience with Fivetran, including pipeline setup, connectors, and transformations
- Experience with cloud platforms; Azure preferred, AWS or GCP also considered
- Solid understanding of CI/CD principles and tools
- Familiarity with Hadoop, Hive, HBase, object storage such as ADLS/S3, and event queues
- Strong understanding of partitioning, clustering, caching, and other performance optimization techniques
- Proficiency with SQL, key-value datastores, and document stores
- Familiarity with data architecture and modeling concepts
- Advanced understanding of data normalization and denormalization
- Ability to translate enterprise requirements into effective data models
- Experience designing, building, and optimizing scalable batch and streaming pipelines using Databricks, Apache Spark, and Delta Lake to support Medallion Architecture
- Ability to automate workflows and maintain clear documentation for data processes
- Experience with Azure Data Lake Storage, Event Hubs, Azure SQL, and AKS
- Ability to monitor and troubleshoot data pipelines and platform workloads
- Strong collaboration and communication skills; ability to work across multiple teams and disciplines
- Master’s degree in Computer Science, Software Engineering, or related field preferred
- Knowledge of data governance, metadata management, or data quality/observability preferred
- Familiarity with schema design and data contracts preferred
- Experience handling video, audio, and image file formats preferred
- Experience with Databricks, Snowflake, or similar platforms preferred
- Must not require GM immigration-related sponsorship now or in the future, including H-1B, OPT, STEM OPT, CPT, TN, and J-1 sponsorship
Benefits
Comp & perks- Bonus potential through an incentive pay program based on company, job-level, and individual performance
- Health and wellbeing benefit programs
- Medical, dental, and vision coverage
- Health Savings Account
- Flexible Spending Accounts
- Retirement savings plan
- Sickness and accident benefits
- Life insurance
- Paid vacation and holidays
- Tuition assistance programs
- Employee assistance program
- GM vehicle discounts
- Relocation benefits may be available