AWS Data Engineer

Senior AWS Cloud Data Engineer

Skills: AWS, data engineer, AWS Glue, data lake, etc Must be local to NJ Must have at least 10 years of experience

Job Requirements

• Databricks, delta lake, AWS building data pipelines and data processing solutions based on AWS platform, & Python
• Must have Data Bricks, AWS, Python or PySpark development experience

Strong experience in relational and non-relational data architecture

Strong experience in data classification based on data type

Strong experience in working with data scientists, architects, and business experts to clarify requirements for components and features of the Data Lake. Ability to garner requirements for varying consumers of Data Lake is strongly desired.

Strong expertise in designing, and developing metadata-driven Data Lake solutions for ingesting historic and near real-time structured/semi-structured/unstructured data

10 years or more experience in data management

Minimum 2 years of experience managing changes in enterprise-grade operational Data Lake

Hands-on experience developing systems that leverage multiple AWS services including CloudFormation, Lambda, API Gateway, S3, DynamoDB/ any NoSQL, Relational Database Service (RDS), Glue Catalog, Crawler, Glue ETL job, Athena and QuickSight for data management and analysis

Strong experience in design & implement ETL and ELT pipelines is a must

Experience in AWS EMR is plus

Expertise in using tools like Gliffy to create diagrams representing Business Process, ERD and AWS Architecture is a PLUS

Experience in developing solutions for data Ingestion, Transformation, Cataloging, In-Place Querying, Storage, and Security using AWS tools and best practices

Experience in Relational/NOSQL database into an Enterprise Data Lake is a Plus

Experience in setting up AWS CloudWatch, CloudTrail for monitoring and Optimizing the Data Lake environments is a PLUS

Proficient in Python, PySpark, AWS Glue ETL jobs

SQL queries using AWS Athena and mapping of various relational DB queries to Athena

Experience in de-normalizing/flattening data structures in Parquet/ORC is nice to have

Good understanding of AWS IAM policies to implement security best practices in DataLake

Follow and enforce strict standards for code quality, automated testing, infrastructure-as-code and code maintainability

Robust debugging skills and knowledge of automated testing platforms and unit tests

Ability to work in an agile collaborative environment, take lead on developing Stories and translating requirements to Problem Statement

Experience using Agile collaboration tools like Jira, Confluence

Strong analytical skills, problem solving aptitude and strong presentation/communications skills

AWS Certification plus