Senior Data Engineer

Pyramid Consulting, Inc; México; Híbrido; MXN 600.000 - 900.000; Jornada completa

Descripción de la vacante

Pyramid Consulting, Inc. is seeking an experienced data engineering contributor who can work hands-on with Python, data pipelines, and Airflow on AWS. You will build and maintain reusable Python packages, automate ETL jobs, and optimize SQL for data warehouses while implementing DBT tests and CI/CD pipelines.

The role requires extensive experience with S3, IAM, and cloud-based data storage, plus the ability to orchestrate complex workflows and monitor pipeline health in a scalable environment.

Formación

• Advanced Python concepts including structures, modules, classes, inheritance and multi-threading.
• Experience building reusable Python packages for internal or public use.
• Ability to automate ETL processes and schedule jobs with Airflow DAGs.
• Track and reprocess failed job records in pipelines.
• Coordinate orchestration of pipelines in sequence or parallel.
• Troubleshoot data pipeline errors and fix issues.
• Export/import data to/from CSV, JSON, XML, preferably from S3 or similar storage.
• Proficiency with AI IDE tools is a plus.
• Advanced SQL including joins, CTEs and subqueries; optimize queries for data warehouses.
• Testing and documentation: Python unit/integration/system tests; DBT data quality tests.
• Code generation using Python and Jinja templates.
• GitHub usage including CI/CD implementation from scratch.
• AWS data storage (S3), ECS, IAM, security best practices and DBT profiles access.

Responsabilidades

• Develop reusable Python packages for internal or public usage.
• Produce automated ETL pipelines and manage Airflow DAGs.
• Monitor and reprocess failed pipeline runs.
• Orchestrate multiple pipelines to run in sequence or in parallel.
• Troubleshoot and fix data pipeline errors and performance issues.
• Export/import data to/from formats like CSV/JSON/XML from cloud storage.
• Implement DBT tests for data validation and quality checks.
• Create code using configurations via Python and Jinja templates.
• Implement CI/CD pipelines with GitHub for automated deployments.
• Integrate Airflow with AWS services and DBT models, triggering DBT jobs or data moves.

Conocimientos

Python programming

Data pipelines

Airflow

ETL development

SQL mastery

CI/CD

GitHub

Herramientas

Airflow on AWS

DBT

GitHub CI/CD

S3 & AWS IAM

Redshift / EMR

Descripción del empleo

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 Client

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

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 Client. 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