**SUMMARY**
**RESPONSIBILITIES**
- Build and maintain ELT pipelines in Google Cloud that land, transform, and publish data to BigQuery from internal systems and third-party sources using Cloud Storage, scheduled queries, and lightweight serverless jobs with Cloud Scheduler and Cloud Functions or Cloud Run.
- Design and document datasets, tables, and views that support analytics use cases in marketing, including clear naming, partitioning and clustering, and performance considerations.
- Contribute to Looker by adding or refining LookML models, dimensions, measures, and Explores, and by maintaining dashboards with sensible refresh and performance settings.
- Implement data quality checks and basic alerting for pipeline health and data completeness.
Maintain runbooks and respond to incidents with timely fixes and clear communication.
- Partner with Marketing and IT to translate requirements into technical tasks, propose simple solution designs, estimate effort, and track delivery.
- Integrate identifiers and events from multiple systems, aligning schemas and keys, defining update and merge rules, and keeping profiles current for activation and measurement needs.
- Use modern AI assistants when appropriate to accelerate routine tasks such as drafting SQL, documenting changes, or generating tests.
**REQUIREMENTS**




- **Degree**:BA or BS in Computer Science, Information Systems, Engineering, Statistics, or equivalent practical experience through internships, capstone projects, or personal projects.
- **Years of experience**:0 to 2 years in data engineering, analytics engineering, or business intelligence.
- **Required technical skills**:
**-**SQL in BigQuery, including joins, window functions, common table expressions, and performance basics.
**-**Google Cloud fundamentals for data work, including BigQuery, Cloud Storage, IAM basics, and scheduling with Cloud Scheduler.
**-**Version control with Git and GitHub, including branching and pull requests.
**-**Data modeling concepts that support analytics, including star or snowflake patterns and pragmatic table design.
- **Preferred skills**:
**-**Looker and LookML for semantic modeling and dashboards.
**-**Dataform or dbt for ELT orchestration and testing.
**-**Airflow or Cloud Composer familiarity.
**-**Python or a similar language for utilities, API integrations, or data quality checks.
**-**Working with REST and JSON for vendor data feeds.
**-**Experience using AI assistants for coding and documentation and interest in Vertex AI.
- **Other**:Proficient in English (written and spoken)

📌 Jr Data Engineer (Chihuahua)
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