Senior Data Analytics Engineer
2 weeks ago
How is this Team contributing to the vision of Providence:
The Marketing Analytics team at Providence works alongside marketing managers, marketing technology, and executives in providing reporting and insights measurements that tell the effectiveness and financial outcome all marketing activity and the consumer journey overall.
What will you be responsible for?
As a Senior Data Analytics Engineer, we are seeking a highly skilled Machine Learning Operations (MLOps) and Data Engineer to join our team. In this role, you will be responsible for building and maintaining the infrastructure required to support our machine learning models and data pipelines. You will work closely with data scientists, machine learning engineers, and software engineers to ensure that our models can be deployed and scaled efficiently and reliably, and that our data pipelines are reliable, scalable, and secure.
What would your day look like?
- Design, build, and maintain the infrastructure required to support our machine learning models and data pipelines
- Collaborate with data scientists, machine learning engineers, and software engineers to ensure that our models can be deployed and scaled efficiently and reliably
- Implement and maintain CI/CD pipelines for machine learning models and data pipelines
- Automate the deployment and scaling of machine learning models and data pipelines in production environments
- Ensure that our machine learning models and data pipelines are secure and comply with regulatory requirements
- Build and maintain data pipelines, including data ingestion, data transformation, and data storage
- Monitor the performance of our machine learning models and data pipelines and implement improvements to optimize performance
- Stay up-to-date with the latest developments in MLOps and identify opportunities to improve our processes and infrastructure
Who are we looking for?
- Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field; Master's degree preferred
- 5-8 years of experience in MLOps, DevOps, or related field with large scale enterprise
- Strong programming experience in multiple programming languages (java/j2ee/python/Nodejs/PowerShell)
- Knowledge of SQL and NoSQL databases
- Strong understanding of machine learning concepts and techniques
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
- Expert in monitoring & APM tools such as DataDog, Azure Log Analytics, Splunk, New relic, Nagios, Graphite, Grafana etc.
- High Proficiency on cloud technologies & infrastructure, preferably Azure
- Experience with Databricks and Snowflake
- Experience with Snowflake's Snow Pipes and Azure Data Factory (ADF)
- Experience building and maintaining data pipelines using technologies such as Apache Spark, Apache Kafka, and/or Apache Airflow
- Strong understanding of distributed systems and experience with cloud-based platforms such as AWS, Azure, or GCP
- Experience with containerization technologies such as Docker and Kubernetes
- Experience with data storage and management systems such as Apache Hadoop, Spark, or Cassandra
- Excellent problem-solving skills and ability to work independently
- Strong communication skills and ability to work in a team environment
- Experience with configuration management tools such as Ansible or Chef
- Experience with monitoring and logging tools such as Prometheus or Elasticsearch/Kibana
- Prior experience in Marketing analytics/Healthcare industry is preferred
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