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Data Engineer
GM Financial. Work internal business partners to identify, capture, collect, and format data from the external sources, internal systems and the data warehouse to extract features of interest .
Tech Stack
Tools & technologiesAWSAzureCassandraCloudDistributed SystemsETLGoogle Cloud PlatformGradleHadoopHDFSKafkaKubernetesMavenMongoDBNoSQLOracleRedisSparkSubversionTerraformWebpack
About the role
Key responsibilities & impact- Work internal business partners to identify, capture, collect, and format data from the external sources, internal systems and the data warehouse to extract features of interest
- Contribute to the evaluation, research, experimentation efforts with batch and streaming data engineering technologies in a lab 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
- 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 problem solve data availability and activation issues
Requirements
What you’ll need- 0-2 years of hands on experience with data engineering required
- Bachelor’s Degree in related field or equivalent experience required
- Experience with processing large data sets using Hadoop, HDFS, Spark, Kafka, Flume or similar distributed systems
- Experience with ingesting various source data formats such as JSON, Parquet, SequenceFile, Cloud Databases, 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
- Working knowledge of Object Storage technologies to include but not limited to Data Lake Storage Gen2, S3, Minio, Ceph, ADLS etc
- Experience with containerization to include but not limited to Dockers, Kubernetes, Spark on Kubernetes, Spark Operator
- Strong background with source control management systems (GIT or Subversion); Build Systems (Maven, Gradle, Webpack); Code Quality (Sonar); Artifact Repository Managers (Artifactory), Continuous Integration/ Continuous Deployment (Azure DevOps)
- Experience with NoSQL data stores such as CosmosDB, MongoDB, Cassandra, Redis, Riak or other technologies that embed NoSQL with search such as MarkLogic or Lily Enterprise
- Creating and maintaining ETL processes
- Experience with Adobe solutions (ideally Adobe Experience Platform, DTM/Launch) and REST APIs
- Understanding of cloud solutions such as Google Cloud Platform, Microsoft Azure & Amazon AWS cloud architecture & services
- Understanding of GDPR, privacy & security topics.
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
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringHadoopHDFSSparkKafkaFlumeJSONParquetETL processesNoSQL
Soft Skills
problem solvingcollaborationcommunication
Certifications
Bachelor’s Degree