Analytics Engineering Manager, Data Platform & Governance
New
J
JobgetherData platform
Based in BrazilFull-TimeManager
Salary75,000 - 120,000 USD per year
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Job Details
- Required Skills
- SQLApache Airflowdbt
Requirements
- Have hands-on experience in analytics engineering, data engineering, data platform management, or a closely related discipline, including responsibility for data quality and governance.
- Have experience managing or being accountable for other people’s work, including setting priorities, allocating responsibilities, and overseeing delivery.
- Bring strong technical expertise in data warehouses and pipeline technologies, particularly Amazon Redshift, dbt, and Airflow.
- Have practical experience with data ingestion tools such as Fivetran and custom Airflow pipelines.
- Have experience managing BI platforms and governance practices at company scale, including workspace administration, permissions, reporting standards, and self-service enablement.
- Be familiar with event-tracking platforms such as Segment, including event catalogs, naming conventions, property dictionaries, and tracking quality controls.
- Understand data lineage, schema changes, impact analysis, freshness monitoring, anomaly detection, and automated data quality checks.
- Have experience with semantic layers and metric governance, and the ability to establish data contracts with engineering teams.
- Have strong SQL skills and be able to investigate data issues, debug pipelines, configure permissions, and implement technical solutions directly.
- Have experience building automated monitoring and quality controls, and daily familiarity with AI tools such as Claude Code, Copilot, or ChatGPT.
- Be able to turn stakeholder requests into a prioritized technical roadmap and establish standards across teams.
- Be comfortable working independently in a remote, asynchronous environment.
Responsibilities
- Own the data platform and governance roadmap, gathering requirements and prioritizing initiatives across product, marketing, operations, and finance.
- Establish automated data quality and freshness monitoring across source systems, pipelines, warehouse models, and reports.
- Manage data incidents and improve detection, prevention, and response processes.
- Build and maintain end-to-end data lineage and impact analysis across production sources, warehouse models, dashboards, and event tracking.
- Partner with engineering teams to introduce data contracts and breaking-change detection in development and release workflows.
- Lead the migration to Lightdash and define workspace structure, permissions, naming conventions, certification standards, and governance practices.
- Maintain the semantic layer and consistent definitions for business-critical metrics.
- Govern the Segment event catalog, including event reviews, naming standards, property definitions, and drift detection.
- Oversee data security and privacy practices, including access controls, PII handling, retention policies, and access reviews.
- Develop governance documentation, ownership models, monitoring, and review processes; help recruit and develop a Lead Analytics Engineer as the team grows.
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