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 integrate Airflow with AWS services and DBT models such as triggering a DBT model or EMR or reading from s3 writing to redshift or snowflake.

Experience in API integrations to Salesforce, SFTP, SharePoint, One Drive and others. DBT Core/ Cloud Proficiency (nice to have): Experience in creating complex DBT models including full refresh, incremental models, snapshots, and documentation. Ability to write and maintain DBT macros for reusable code Experience in creating custom DBT macros using jinja and Python allowing for reusable components within DBT models Monitoring and Logging (nice to have): Familiarity with AWS cloud watch, Data Dog for monitoring the pipelines and setting up alerts for workflow failures

📌 AWS Data Engineer (México)
🏢 Valce Talent Solutions
📍 México