Lead Data Engineer, Azure

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

📋 Description

• Comprehend client needs and spearhead the development of robust data platforms utilizing Data Lakehouse architectures, acting as the key subject matter expert for the Azure data ecosystem (Microsoft Fabric, Azure SQL, and Power BI).

• Create and execute scalable data models, ETL/ELT pipelines, and analytics layers within contemporary cloud environments.

• Design Microsoft Fabric reporting solutions, implementing medallion layering, managing capacity planning, ensuring freshness governance, and setting up CDC/mirroring from Azure SQL into Fabric.

• Implement stringent data-layer segregation to exclude PII by design, ensure multi-tenant isolation within the analytics layer, and comply with 10+ year regulated data retention policies.

• Oversee complex migration initiatives from legacy systems (e.g., AirTable, Smartsheet) to Microsoft Fabric, adeptly managing mid-program form and rule drift, while establishing reliable, per-client export channels.

• Direct comprehensive analytics projects — from requirements gathering through to deployment.

• Mentor junior team members, conduct code reviews, and guarantee compliance with quality standards. Collaborate closely with cross-functional teams (engineering, product, business) to align data strategies with business objectives.

• Develop and enhance intricate SQL queries, Power BI semantic models, dashboards, and reports (transitioning from legacy LookML/BigQuery paradigms).

• Diagnose performance bottlenecks, data discrepancies, and integration issues.

• Remain informed on the latest advancements in the analytics and cloud data ecosystem.

• Foster innovation in reporting and analytics capabilities. Suggest and deploy new tools, frameworks, and practices to upgrade the data platform.

• Establish best practices, coding guidelines, and governance for analytics projects.

• Track data systems performance and implement optimization strategies.

• Guarantee data accuracy, integrity, privacy, security, and compliance through robust quality control procedures.

• Construct and manage AI-ready data pipelines, aimed at supplying scrubbed, segmented data to assistive AI (embeddings, vector stores, and feature stores) and incorporating GenAI into analytics and data products.

• Promote the adoption of AI-assisted data engineering across the team: copilots for SQL/transformation/pipeline code, alongside automated testing and documentation.

• Set governance and quality standards for data utilized by LLMs and agents.

⛳️ Requirements

• Proven expertise with at least 7 - 10 years of relevant experience in data engineering and business intelligence.

• Strong primary proficiency in the Azure Data Stack, particularly Azure SQL, Microsoft Fabric, and Power BI (semantic layer design, robust dashboard development), with no less than two years of hands-on experience using these specific tools.

• Advanced SQL capabilities and a thorough understanding of modern data architecture, including Data Lakehouse concepts, medallion architecture, star/snowflake schemas, and dimensional modeling.

• Proficiency in Python for data engineering, ETL/ELT workflows, and automation tasks.

• Experience in designing and managing enterprise-grade data pipelines — particularly in Azure environments.

• Documented success in leading analytics projects and delivering scalable data solutions.

• Ability to serve as a player-coach — leading while also being actively involved.

• Comprehensive understanding of data governance, security (especially regarding PII and multi-tenant architectures), and performance optimization practices.

• Strong communication skills with the ability to convey complex technical concepts to business stakeholders.

🏝️ Benefits

• Medical Insurance benefits as per company policy.

• Life Insurance as per company policy.

• 15 days of paid vacation plus additional days based on tenure.

• Vacation bonus as per local law.

• Sick leave and paid holidays as per local law.

• Profit sharing as per local law.

• Paternity and maternity leave as per local law.

• Marriage, bereavement, and graduation leaves as per company policy.

• Christmas bonuses as per local law.

• Work from home allowance as per company policy.

• Punctuality and attendance bonuses as per company policy.

• Food tickets as per company policy.

• Direct deposit of payroll.

• Paid professional certifications.