Analytics Engineering Manager

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and implement analytics strategies, KPI frameworks, and data product standards across various teams.

• Oversee the enterprise semantic and reporting layer strategy for QuickSight/Tableau and Redshift/Athena.

• Collaborate with data engineering and architecture teams on domain models, data contracts, and self-service analytics capabilities.

• Create and enforce data quality, documentation, and review processes.

• Manage escalation and resolution pathways for analytics-related issues.

• Lead and provide mentorship to analysts.

• Oversee capacity management, prioritization, and quality across multiple projects.

• Convey insights and trade-offs to executive leadership.

• Facilitate decision-making through clear narratives and measurable results.

• Enhance the cost-effectiveness and performance of analytical workloads.

• Suggest storage and query patterns, including those for Redshift, Athena, and row-level caching.

• Ensure adherence to data governance, privacy, and security standards.

• Manage access policies in collaboration with platform teams.

⛳️ Requirements

• A degree is required for the visa application process.

• Experience in leading analytics programs and teams.

• Proven ability to communicate effectively with stakeholders and executives.

• Expertise in SQL and performance engineering specifically on Redshift.

• In-depth knowledge of Athena/S3, including partitioning, Parquet/ORC, and Glue cataloging.

• Proficient in BI architecture and governance in QuickSight/Tableau, including semantic layers and certification processes.

• Advanced skills in Python for analytics automation, reproducibility, and standards.

• Comprehensive understanding of dimensional modeling, domain-driven design for analytics, and metric governance.

• Strong background in data quality frameworks, documentation practices, and analytics SDLC, including versioning, review, and release processes.

• Demonstrated resilience, emotional intelligence, and a focus on agile delivery.

• Thorough understanding of the differences between coding and engineering.

• Experience in influencing data platform architecture decisions.

• Familiarity with Redshift Spectrum, RA3 architecture, and concurrency scaling.

• Exposure to cost optimization and workload management at scale.

• Experience in capacity planning and defining SLAs.

• Good understanding of AI tools such as GitHub Copilot or similar.

• Familiarity with cloud-native foundations or AI coding assistants.

• Advanced proficiency in oral English.

• Advanced proficiency in Spanish.

🏝️ Benefits

• Flexible remote work options.

• Opportunities for continuous learning.

• Involvement in high-impact projects and complex engineering challenges.

• Opportunities for growth and professional development.

• International collaboration across global delivery centers.