Delivery Consultant - Data Analytics, US Federal ProServe

Amazon; Seattle (WA); On-site; USD 90,000 - 150,000; Full time

Job summary

An established industry player is seeking a skilled Data Analytics Consultant to help U.S. Federal agencies leverage innovative cloud computing solutions. This role involves designing and implementing data warehouse infrastructure using AWS technologies, developing ETL pipelines, and collaborating with various teams to enhance analytics capabilities. The ideal candidate will have a strong background in data engineering, excellent communication skills, and a passion for working with large datasets. Join a collaborative team that values innovation and empowers you to make a significant impact in the field of data analytics.

Qualifications

• 3+ years of data engineering experience with a strong focus on AWS technologies.
• Experience in building ETL pipelines and data modeling for analytics.

Responsibilities

• Design and support data warehouse infrastructure using AWS big data stack.
• Develop ETLs and manage data pipelines for analytics and reporting.

Skills

Data Engineering

Data Modeling

ETL Pipelines

SQL

Business Intelligence

Data Visualization

Python Programming

Data Analysis

Education

Bachelor's degree in Computer Science

Master's degree in Computer Science

Tools

AWS Redshift

AWS Glue

AWS EMR

AWS QuickSight

AWS S3

AWS Kinesis

Job description

Delivery Consultant - Data Analytics, US Federal ProServe

Do you like helping U.S. Federal agencies implement innovative cloud computing solutions and solve technical problems? Would you like to do this using the latest cloud computing technologies? Do you have a knack for helping these groups understand application architectures and integration approaches, and the consultative and leadership skills to launch a project on a trajectory to success? Amazon Web Services (AWS) Professional Services engage in a wide variety of projects for customers and partners, providing collective experience from across the AWS customer base and are obsessed about strong success for the Customer. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based upon customer needs.

We are looking for an experienced, self-driven Data Analytics Consultant. In this role, you will be building complex data engineering and business intelligence applications using AWS big data stack. You should have deep expertise and passion in working with large data sets, data visualization, building complex data processes, performance tuning, bringing data from disparate data stores and programmatically identifying patterns. You should have excellent business acumen and communication skills to be able to work with business owners to develop and define key business questions and requirements.

It is expected to work from one of the above locations (or customer sites) at least 1+ days in a 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 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

1. Design, implement, and support data warehouse/data lake infrastructure using AWS big data stack, Python, Redshift, QuickSight, Glue/lake formation, EMR/Spark, Athena etc.
2. Develop and manage ETLs to source data from various financial, AWS networking and operational systems and create unified data model for analytics and reporting.
3. Creation and support of real-time data pipelines built on AWS technologies including EMR, Glue, Redshift/Spectrum and Athena.
4. Collaborate with other Engineering teams, Product/Finance Managers/Analysts to implement advanced analytics algorithms that exploit our rich datasets for financial model development, statistical analysis, prediction, etc.
5. Continual research of the latest big data and visualization technologies to provide new capabilities and increase efficiency.
6. Use business intelligence and visualization software (e.g., QuickSight) to develop dashboards used by senior leadership.
7. Empower technical and non-technical internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
8. Work closely with team members to drive real-time model implementations for monitoring and alerting of risk systems.
9. Manage numerous requests concurrently and strategically, prioritizing when necessary.
10. Partner/collaborate across teams/roles to deliver results.
11. Mentor other engineers, influence positively team culture, and help grow the team.

Minimum Requirements

• 3+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with SQL
• Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with non-relational databases/data stores (object storage, document or key-value stores, graph databases, column-family databases)
• Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
• Prior experience in programming using Python

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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