Mueller Water Products · 16 hours ago

AWS Data Engineer (Non-Sponsorship Eligible Role)

Atlanta, GA

Full-time

Remote

Mid Level

3+ years exp

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Responsibilities

Design, Build and Operate the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, cloud migration tools, and ‘big data’ technologies.

Optimize various RDBMS engines in the cloud and solve customers' security, performance, and operation problems.

Design, Build, and Operate large, complex data lakes that meet functional / non-functional business requirements.

Optimize various data types of ingestion, storage, processing, and retrieval from near real-time events, and IoT, to unstructured data as images, audio, video, and documents, and in between.

Work with customers' and internal stakeholders including the Executive, Product, Data, Software Development, and Design teams to assist with data-related technical issues and support their data infrastructure and business needs.

Understand and Develop AI/ML models using AWS AI/ML services (e.g., Sage Maker, Rekognition, Comprehend) and collaborate with data scientists and engineers to implement machine learning solutions.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

AWS Glue ETLData pipelinesData LakePythonAWS RedshiftAWS Step FunctionAWS AthenaSparkRelational databasesNoSQL databasesAdvanced SQLCI/CD pipelinesLake Formation OrchestrationData warehousingDimensional modeling

Required

3+ years of experience in a Data Engineer role in a cloud-native eco-system.

Bachelor (Graduate preferred) degree in Computer Science, Mathematics, Informatics, Information Systems, or another quantitative field.

3+ years working experience in AWS Glue ETL, Redshift, Step Function, Athena

Experience in implementing data pipelines for both streaming and batch integrations using tools/frameworks like Glue ETL, Lambda, Spark, Spark Experience in Lake Formation Orchestration, Maintain and enhance models for SDLC using CI/CD pipelines in AWS.

Experience in Relational and NoSQL databases, such as MySQL or Postgres and DynamoDB.

Functional and scripting languages: Python, Advanced SQL.

Experience building and optimizing ‘big data’ pipelines, architectures, and data sets.