Senior Data Analytics Engineer

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