Lead Data Engineer, Azure

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

📋 Description

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

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

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

• Implement strict data-layer segregation to ensure PII is excluded by design, maintain multi-tenant isolation in the analytics layer, and strictly follow 10+ year regulated data retention policies.

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

• Direct end-to-end analytics projects — from gathering requirements to deployment.

• Provide mentorship to junior team members, conduct code reviews, and ensure adherence to established 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 frameworks).

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

• Remain informed about developments in the analytics and cloud data landscape.

• Promote innovation in reporting and analytics functionalities. Recommend and execute new tools, frameworks, and practices to improve the data platform.

• Establish best practices, coding standards, and governance for analytics initiatives.

• Monitor the performance of data systems and apply optimization strategies.

• Guarantee data accuracy, integrity, privacy, security, and compliance through rigorous quality control processes.

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

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

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

⛳️ Requirements

• Proven expertise with a minimum of 7 - 10 years of pertinent experience in the data engineering and business intelligence domain.

• Strong primary expertise in the **Azure Data Stack, particularly Azure SQL, Microsoft Fabric**, and Power BI (semantic layer design, advanced dashboard development), with at least two years of hands-on experience in these specific tools.

• Advanced SQL capabilities and a thorough understanding of contemporary 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 maintaining enterprise-grade **data pipelines** — specifically within Azure environments.

• Demonstrated history of **leading analytics projects** and delivering scalable data solutions.

• Capability to act as a **player-coach** — leading while also contributing hands-on.

• Strong grasp of **data governance, security** (especially concerning PII and multi-tenant architectures), and **performance optimization** practices.

• Exceptional communication skills and 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, sick leave, and paid holidays as per local law.

• Paternity and maternity leave as per local law.

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

• Sick leave and paid holidays as per local law.

• Christmas and mid-year bonuses as per local law.

• Monthly productivity bonus as per local law.

• Discounts in local shops.

• Direct deposit of payroll.

• Paid professional certifications.