Description:

Analytica is seeking a remote Data Engineer (MLOps) to support dynamic, long-term federal government enterprise data programs.
The ideal candidate will lead the architecture and implementation of on-premises and cloud big data solutions as part of enterprise data modernization.
Responsibilities include building out data pipelines in AWS for data lakes and data warehouses.
The candidate will implement data pipelines using various tools including Amazon S3, AWS Glue, Amazon Textract, Amazon Comprehend, AWS Lambda, SQL, and/or Python scripts.
The role involves implementing data pipelines for batch and streaming data sources from external feeds into a cloud-based data lake and eventually into data warehouses.
The candidate will also implement data cataloging to share metadata information for datasets in the data lake.
The use of AWS serverless components in the data pipeline architecture is required.
The candidate will utilize Infrastructure as Code (IaC) tools to deploy the pipelines within AWS.

Requirements:

Candidates must have 5+ years of hands-on Data Integration experience creating and maintaining efficient scripts/data pipelines to clean, transform, and ingest data from various formats into database tables, data warehouses, or data lake repositories.
Experience building data pipelines using AWS serverless components is required, including using AWS Glue to build, maintain, and monitor ETL jobs.
Proficiency in using Python to implement ETL scripts and AWS Secrets Manager to manage credentials is necessary.
Experience with AI/ML, NLP, Sentiment Analysis, etc., with one of the leading cloud providers is a plus.
An AWS ML Certification or AWS Data Engineer Certification is desired.
Candidates must be U.S. Citizens.
The ability to obtain and maintain a Public Trust security clearance is required.