Overview
Remote
Depends on Experience
Contract - W2
Contract - Independent
Skills
Dataops
Job Details
Dataops Engineer
Location: remote
Long Term Contract
Senior Engineer, DataOps
Bachelor's degree in computer science, information technology, or related field or equivalent work experience.
7+ years of hands-on experience as DataOps Engineer in a manufacturing or automotive environment.
Experience with streaming and event-based architecture.
Proficient in building data pipelines using languages such as Python and SQL.
Experience with AWS based data services such as Glue, Kinesis, Firehose or other comparable services.
Experience with Structured, unstructured and time series databases.
Solid understanding of cloud data storage solutions such as RDS, DynamoDB, DocumentDB, Mongo, Cassandra, Influx.
Experience implementing data lakehouse solutions using Databricks.
Several years of experience working with cloud platforms such as AWS and Azure.
Experience with infrastructure as code (Terraform).
Proven ability to develop and deploy scalable ML models.
Hands-on experience in designing, training, and deploying ML models
Strong ability to extract actionable insights using ML techniques
Ability to leverage ML algorithms for forecasting trends and decision-making
Excellent problem-solving and troubleshooting skills. When a problem occurs, you run towards it not away.
Effective communication and collaboration skills. You treat colleagues with respect. You have a desire for clean implementations but are also humble in discussing alternative solutions and options
Location: remote
Long Term Contract
Senior Engineer, DataOps
Bachelor's degree in computer science, information technology, or related field or equivalent work experience.
7+ years of hands-on experience as DataOps Engineer in a manufacturing or automotive environment.
Experience with streaming and event-based architecture.
Proficient in building data pipelines using languages such as Python and SQL.
Experience with AWS based data services such as Glue, Kinesis, Firehose or other comparable services.
Experience with Structured, unstructured and time series databases.
Solid understanding of cloud data storage solutions such as RDS, DynamoDB, DocumentDB, Mongo, Cassandra, Influx.
Experience implementing data lakehouse solutions using Databricks.
Several years of experience working with cloud platforms such as AWS and Azure.
Experience with infrastructure as code (Terraform).
Proven ability to develop and deploy scalable ML models.
Hands-on experience in designing, training, and deploying ML models
Strong ability to extract actionable insights using ML techniques
Ability to leverage ML algorithms for forecasting trends and decision-making
Excellent problem-solving and troubleshooting skills. When a problem occurs, you run towards it not away.
Effective communication and collaboration skills. You treat colleagues with respect. You have a desire for clean implementations but are also humble in discussing alternative solutions and options
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.