Sr. Analytics Engineer - Data Platform
J
JobgetherData Platform / Security
MexicoFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- Native Spanish and professional English proficiency
- Experience
- 4+ years of professional experience in data, analytics engineering, data engineering, or BI
- Required Skills
- PostgreSQLPythonSQLGitAirflowData modelingdbt
Requirements
- 4+ years of professional experience in data, analytics engineering, or BI.
- At least 2 years operating as a senior contributor or technical reference.
- Advanced SQL skills and expertise in dimensional modeling.
- Proven experience with dbt or equivalent for production data transformations.
- Experience building data pipelines using Python with best practices like Git and CI/CD.
- Hands-on experience with orchestration platforms like Dagster or Airflow.
- Familiarity with managed ingestion tools such as Airbyte or Fivetran.
- Experience with PostgreSQL or cloud data warehouses (Redshift, Snowflake, BigQuery).
- Experience building semantic layers in BI tools (e.g., Omni, Looker, Hex, Metabase, Power BI).
- Strong communication skills for translating business questions into metric definitions.
- Experience mentoring and establishing technical standards.
- Native Spanish proficiency and professional English proficiency.
Responsibilities
- Design and operate data contracts for critical metrics and datasets using dbt.
- Own analytical data modeling, including data layers, conventions, and dimensional models.
- Strengthen the data platform by managing ingestion, orchestration, quality, and observability.
- Build proactive monitoring and quality processes to identify anomalies.
- Enable self-service analytics through semantic layers and models in tools like Omni and Hex.
- Deliver high-confidence dashboards and reports for leadership and regulatory requirements.
- Collaborate cross-functionally to establish standards for data contracts, quality, and modeling.
- Mentor team members and drive engineering standards through code reviews and pairing.
- Support Data Science and ML initiatives by developing reliable datasets and feature pipelines.
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