Data Engineer, Data and Machine Learning, WWPS U.S Federal ProServe

- 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.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,200/year in our lowest geographic market up to $204,300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Are you excited to help the US Intelligence Community leverage the volume and variety of their data and enable analytics in mission workflows? Do you have a knack for helping these groups design data architectures and and build large-scale, high-volume, high-performance data integration and delivery services, with the consultative and leadership skills to launch a project on a trajectory to success? The Amazon Web Services (AWS) US Federal Professional Services team works directly with US intelligence community agencies and other public sector entities to achieve their mission goals by making the best use of their data. We build data platforms that optimize the transport, conditioning, and governance of all types of data for analytic, machine learning, and data science applications.

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.

It is expected to work from one of the above locations (or customer sites) Monday through Friday each week. This is not a remote position. You are expected to be in the office or with customers as needed.

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.
- Collaborate with engineers/scientists to help adopt best practices in data system creation, data integrity, test design, analysis, validation, governance, and documentation.
- Help continuously improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers.

About the team
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

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.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

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.