Amazon Data Engineer Machine Learning WWPS US Federal ProServe 

United States, Kansas 

416770903

In this role, you will work closely with national security customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their business goals. You should have deep expertise building complex data orchestrations at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data engineering.This position requires that the candidate selected be a US Citizen and must currently possess and maintain an active TS/SCI security clearance with polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work.Key job responsibilities
As a Data Engineer, you are proficient in developing and deploying data pipelines at scale. You should have a passion for working with large data sets, creating data visualizations, building complex data processes, performance tuning, combining data from disparate stores and programmatically identifying patterns. You will work alongside scientists and engineers to implement data orchestrations for production analytic, machine learning, and data science systems.The primary responsibilities of this role are to:
- Design, implement, and support data warehouse/data lake infrastructure using the AWS Big Data stack - Python, Redshift, QuickSight, Glue/Lake Formation, EMR/Spark, Athena etc.
- Implement data ingestion routines both real time and batch using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.
- Design, implement, and operate large-scale, high-volume, high-performance data storage and retrieval solutions for analysis and data science.
- Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Work/Life Balance
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- Bachelor's degree in an engineering or technical field.
- 3+ years experience with detailed knowledge of data warehouse technical architecture, infrastructure components, ETL / ELT and analytic tools, data engineering, and large scale data manipulation using distributed computing technologies (e.g. Spark, EMR, Hive, Kafka, RedShift).
- Experience in relational database concepts with a solid knowledge of SQL as well as performance tuning activities for both query, database, and ETL solutions.
- Knowledge of professional software engineering practices and best practices for the software development lifecycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
- Current, active US Government Security Clearance of TS/SCI with Polygraph

- Coding proficiency in Python.
- Industry experience as a Data Engineer, with a track record of maintaining, processing, and extracting value from large datasets.
- Experience leading large scale data engineering and analytics projects, including using AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, and Lambda.
- Experience with non-relational databases / data stores (object storage, document or key value stores, graph databases, columnar databases).
- Experience implementing and managing data governance solutions for comprehensive metadata management, discoverability, lineage, data quality, and access control.