Analytics Lead Manager

Auxis; Bogotá; On-site; COP 167,400,000 - 256,680,000; Full time

Job summary

Auxis leads in Data & Analytics to design and deliver robust global data platforms enabling business solutions and high-quality analytics. The Analytics Lead (Manager) manages a team of analytics engineers delivering trusted, analytics-ready data products, semantic models, and self-service capabilities that turn enterprise data into actionable insight.

This leader defines the analytics roadmap, drives adoption and enterprise data literacy, ensures governed and AI-ready data consumption, and

Qualifications

• Bachelor’s degree in IT/CS/Engineering or analytics.
• Snowflake experience is required.
• Hands-on experience with Power BI and dbt is required.
• Preferred: experience in professional services or client service roles.

Responsibilities

• Align analytics roadmap with enterprise Data & Analytics strategy, business outcomes, and ROI.
• Define analytics service offerings (self-service reporting, curated datasets and semantic models).
• Establish standards for analytics-ready datasets and semantic models with trusted reporting.
• Sponsor data quality and observability for analytics outputs and SLAs for data freshness.
• Ensure governance-by-design across analytics and data consumption.
• Provide executive-level stakeholder management for analytics delivery commitments.

Skills

SQL

Python

Analytics engineering

Power BI

Machine Learning

Data modeling

Education

Bachelor’s degree in information technology, Computer Science, Engineering, Analytics, or related discipline

Tools

dbt

Snowflake

Informatica IDMC

Git

Job description

Job Summary

The Data & Analytics function is dedicated to designing and delivering robust global data platforms that enable business solutions and high-quality analytics. The Analytics Lead (Manager) manages a team of analytics engineers accountable for delivering trusted, analytics-ready data products, semantic models, and self-service capabilities that turn enterprise data into actionable insight. This leader defines the analytics roadmap, drives adoption and enterprise data literacy, ensures governed and AI-ready data consumption, and partners with the Head of Data & Analytics and service line stakeholders to maximize the business value of data across the organization.

Job Summary

The Data & Analytics function is dedicated to designing and delivering robust global data platforms that enable business solutions and high-quality analytics. The Analytics Lead (Manager) manages a team of analytics engineers accountable for delivering trusted, analytics-ready data products, semantic models, and self-service capabilities that turn enterprise data into actionable insight. This leader defines the analytics roadmap, drives adoption and enterprise data literacy, ensures governed and AI-ready data consumption, and partners with the Head of Data & Analytics and service line stakeholders to maximize the business value of data across the organization.

Responsibilities

• Strategy, Roadmap & Service Ownership
• Align the analytics roadmap with enterprise Data & Analytics strategy, business outcomes, and service line priorities, ensuring fit-for-purpose analytics products prioritized by measurable value and ROI.
• Define analytics service offerings (self-service reporting, curated datasets and semantic models, reusable analytics patterns, and tiered service levels).
• Insight Delivery, Quality & Governance
• Establish standards for analytics-ready (gold-layer) datasets, semantic models, and metric definitions to ensure consistent, trusted, and certified reporting.
• Sponsor data quality and observability for analytics outputs, including SLAs for data freshness and availability against consumer expectations.
• Ensure governance-by-design across analytics: standardized access, classification/metadata, end-to-end lineage, retention controls, and certified datasets.
• Partner with Data Governance, Privacy, and Data Owners/Stewards to ensure analytics outputs are accurate, compliant, and responsibly and ethically used.
• Analytics Engineering & Delivery Leadership
• Mature analytics engineering standards, reference patterns, and semantic models across the Medallion (Bronze/Silver/Gold) architecture, leveraging dbt for transformation and Power BI for delivery.
• Drive analytics automation and productivity: CI/CD for analytics assets, semantic-layer reuse, and AI-ready data preparation (including Snowflake Cortex AI enablement).
• Provide executive-level stakeholder management for analytics delivery commitments, intake and prioritization, and escalations.
• Leadership & Talent
• Build and lead a high-performing team of analytics engineers.
• Define operating model, roles, sourcing strategy (including global delivery centers), and technical and analytics career paths.
• Set measurable goals for adoption, data quality, delivery velocity, cost, and user satisfaction.

Skills

• English level B2+
• 10+ years of relevant experience with demonstrated leadership in analytics delivery, analytics engineering, and BI/insight products; 3+ years in leadership or team-lead roles.
• Proven ability to deliver enterprise-grade analytics and self-service capabilities with strong governance and data quality alignment.
• Strong technical breadth across analytics engineering, semantic modeling, BI and visualization (Power BI), cloud data platforms, and modern transformation tooling (dbt).
• Executive communication, storytelling-with-data, and presentation skills.
• Experience building analytics-ready data products and semantic layers at scale (including data quality and observability) and driving adoption and data literacy.
• Experience with Agile delivery, intake and prioritization practices, and Snowflake/Informatica IDMC platform best practices.
• Proven experience with Machine Learning, predictive analytics, and natural language processing.
• Strong programming skills in SQL and Python for data validation, profiling, reconciliation, and analytics.
• Experience with data modeling methodologies (Dimensional modeling, Data Marts, Data Warehousing, Star/Snowflake schema).

Education / Professional Experience/ Qualifications

• Bachelor’s degree in information technology, Computer Science, Engineering, Analytics, or related discipline.
• Snowflake experience is required.
• Hands-on experience with BI and analytics engineering tools (e.g., Power BI and dbt) is required.
• Preferred: Experience in professional services, accounting industry, or client service/consultative technology roles.