Data Engineer II - General Motors Insurance

GM Financial is committed to AI-powered transformation and digital innovation in the financial sector. The Data Engineer II role focuses on ingesting and processing large data sets to support reporting, data science, and analytics, while collaborating with various teams to enhance data engineering practices.

Responsibilities:

• Contribute to the evaluation, research, experimentation efforts with batch and streaming data engineering technologies to keep pace with industry innovation
• Work with data engineering related groups to inform on and showcase capabilities of emerging technologies and to enable the adoption of these new technologies and associated techniques
• Contribute to the definition and refinement of processes and procedures for the data engineering practice
• Work closely with data scientists, data architects, ETL developers, other IT counterparts, and business partners to identify, capture, collect and format data from the external sources, internal systems, and the data warehouse to extract features of interest
• Code, test, deploy, monitor, document and troubleshoot data engineering processing and associated automation

Requirements:

• Experience with processing large data sets using Hadoop, HDFS, Spark, Kafka, Pulsar, Flume or similar distributed systems
• Experience with ingesting various source data formats such as JSON, Parquet, CSV, SequenceFile, Cloud Databases, Document Databases like CosmosDB, MQ, Relational Databases such as Oracle
• Experience with Cloud technologies (such as Azure, AWS, GCP) and native toolsets such as Azure ARM Templates, Hashicorp Terraform, AWS Cloud Formation
• Understanding of cloud computing technologies, business drivers and emerging computing trends
• Thorough understanding of Hybrid Cloud Computing: virtualization technologies, Infrastructure as a Service, Platform as a Service and Software as a Service Cloud delivery models and the current competitive landscape
• Working knowledge of Object Storage technologies to include but not limited to Data Lake Storage Gen2, S3, ADLS etc
• Working knowledge of Agile development /SAFe, Scrum and Application Lifecycle Management
• Strong background with source control management systems (GIT or Subversion); Code Quality (Sonar); Artifact Repository Managers (Artifactory), Continuous Integration/ Continuous Deployment (Azure DevOps)
• Experience with NoSQL data stores such as CosmosDB, MongoDB
• Creating and maintaining ETL processes
• Knowledgeable of best practices in information technology governance and privacy compliance
• Troubleshoot complex problems and works across teams to meet commitments
• Excellent computer skills and proficiency in digital data collection
• Ability to work in an Agile/Scrum team environment
• Strong interpersonal, verbal, and writing skills
• Understanding of big data platforms and architectures, data stream processing pipeline/platform, data lake and data lake houses
• SQL experience: querying data and sharing what insights can be derived
• Understanding of cloud solutions such as Microsoft Azure & Amazon AWS cloud architecture & services
• Understanding of GDPR, privacy & security topics
• Strong in the use of Microsoft Office software, data querying platforms and statistical programming tools such as Python
• 2-4 years of hands-on experience with data engineering required
• Bachelor's degree in related field or equivalent experience required
• Experience in working with vehicle telemetry and auto insurance data is a plus
• Understanding of data management and governance tools like Atlan, Immuta etc. is a plus
• Experience with Adobe solutions (ideally Adobe Experience Platform) and REST APIs
• Databricks is a plus