AWS Data Engineer Remote 10+ Years Experience Great
Communicator/Client Facing/ Attention to detail Individual
Contributor and ability to work as a team. 100% Hands on in the
mentioned skills Programming Skills: Python and Data Pipelines:
Advanced Proficiency in Python concepts like Code Structures,
Modules, Packages, Class, SubClass, Inheritance, Multi-Threading
and Functional Programming. Experience in developing reusable
Python packages for internal or public usage Ability to write
automating ETL processes and scheduling jobs like Airflow DAG.
Ability to track job pipeline runs to reprocess error records
Ability to orchestration different pipelines to run in sequence or
parallel. Troubleshoot data pipeline errors and fix issues Export
or Import data to/from various formats like CSV, JSON, XML etc
preferably from S3 or other cloud storage. Experience in using AI
IDE tool SQL: Advanced SQL skills, including complex joins, CTE's
and subqueries Experience in optimizing SQL queries for performance
and optimization in data warehouse technologies preferably
Snowflake Testing and documentation: Proficiency in Python unit,
integration and system test. Proficiency in implementing DBT tests
for data validation and quality checks Code Generation: Experience
in generating code using configurations using python and jinja
templates Version control: Experience in GitHub, including
implementing CI/CD process from scratch AWS Expertise: Data Storage
solutions: In depth understanding of AWS S3 for data storage, ECS,
IAM including best practices for organization and security Cloud
Security: Knowledge of AWS security best practices, including IAM
roles, encryption standard, secure coding guidelines, DBT profiles
access configurations and more. Data Integration (nice to have):
Experience with AWS lambda for serverless data processing tasks
Workflow Orchestration (nice to have): Proficiency in using Apache
Airflow on AWS to design ,schedule and monitor complex data flows
Ability to int