Data Engineer - MS Fabric & Azure

Role & responsibilities

• Design, build, and own end-to-end data engineering solutions on Microsoft Fabric and Azure that power marketing, sales, and website performance reporting across Asia, EMEA, and the Americas.
• Architect OneLake-based Lakehouse and Warehouse solutions following a medallion (bronze, silver, gold) pattern on Delta tables to deliver curated, analytics-ready datasets.
• Develop and orchestrate scalable batch and incremental ingestion pipelines using Fabric Data Factory, Dataflows Gen2, Spark notebooks, and Azure Data Factory.
• Integrate marketing and sales data sources including Adobe Analytics, Dynamics 365/Dataverse, marketing automation platforms, SQL Server, SharePoint, and third-party REST APIs into a unified data platform.
• Build and optimize Direct Lake, Import, and composite semantic models in partnership with BI developers to support the Power BI dashboard portfolio.
• Lead the migration of legacy SQL Server, SSIS, and SSAS workloads to Microsoft Fabric with minimal disruption to business reporting.
• Implement automated data quality checks, validation rules, and reconciliation controls to safeguard data accuracy across all pipelines.
• Monitor, troubleshoot, and tune pipeline performance, workloads, and Fabric capacity consumption to ensure reliability and cost efficiency.
• Enforce data security, privacy, and governance standards, including access controls, PII handling, sensitivity labels, and lineage through Microsoft Purview.
• Define and maintain engineering standards, reusable frameworks, data contracts, and technical documentation for the data platform.
• Mentor analysts and junior engineers, conduct code reviews, and act as the technical point of contact for data engineering across the global team.
• Partner with Microsoft stakeholders, BI leads, and platform teams to translate reporting requirements into scalable data architecture and delivery roadmaps.

Preferred candidate profile

Microsoft Fabric

• Expert hands-on experience with Microsoft Fabric, including OneLake, Lakehouse, Warehouse, Data Factory pipelines, Dataflows Gen2, and notebooks.
• Experience with OneLake shortcuts and Fabric Mirroring to integrate data from Azure SQL, ADLS Gen2, Dataverse, and other sources without duplication.
• Experience with Fabric capacity management, Capacity Metrics monitoring, workload governance, and workspace administration.
• Proficiency with Fabric deployment pipelines and Git integration for source-controlled, multi-environment releases.

Azure Data Platform

• Strong experience with Azure Data Factory and/or Azure Synapse Analytics pipelines, including parameterization, triggers, and integration runtimes.
• Solid knowledge of Azure Data Lake Storage Gen2, storage design, and file formats such as Parquet, Delta, CSV, and JSON.

SQL & Data Modeling

• Advanced T-SQL expertise on SQL Server, Azure SQL, and Fabric Warehouse, including stored procedures, query tuning, and indexing strategies.
• Experience with SSIS packages and SSAS tabular models, including migration of these legacy workloads to Microsoft Fabric.
• Strong dimensional modeling skills including star schema design, slowly changing dimensions, and fact table design optimized for Power BI consumption.

Power BI

• Experience designing Power BI semantic models in Direct Lake, Import, and composite modes, including row-level security and working knowledge of DAX.

Source Integrations

• Experience ingesting Adobe Analytics data via Data Feeds and APIs and modeling web and campaign performance data.
• Experience integrating Dynamics 365 and Dataverse data, including linking to Microsoft Fabric, for sales pipeline and CRM reporting.

Security & Governance

• Strong understanding of Azure security, including Microsoft Entra ID, managed identities, service principals, Azure Key Vault, and role-based access control.
• Experience with Microsoft Purview for data cataloging, lineage, classification, and sensitivity labels.

Programming

• Strong programming skills in Python and SQL, with working knowledge of KQL and PowerShell for querying and automation.

Domain Knowledge

• Understanding of marketing and sales data domains, including campaign, web analytics, lead, and opportunity pipeline data.

Soft Skills

• Strong ownership and accountability for platform reliability, with a proactive approach to identifying and resolving data issues.
• Ability to translate business and reporting requirements from marketing and sales stakeholders into clear technical designs.
• Clear written and verbal communication, including explaining complex technical concepts to non-technical audiences.
• Strong analytical problem-solving and root-cause analysis skills within complex, multi-source data environments.
• Commitment to engineering excellence, documentation, and knowledge sharing across the global team.
• Mentorship mindset with the ability to coach analysts and junior engineers through code reviews and pairing.
• Effective collaboration across distributed, cross-functional teams and time zones, including the Buenos Aires and Delhi hubs.
• Ability to prioritize and manage multiple concurrent engineering deliverables in a fast-paced environment.
• Continuous learning mindset with curiosity for evolving Microsoft Fabric, Azure, and AI capabilities.

Qualifications & Experience

• 5+ years of hands-on data engineering experience, including at least 3 years building solutions on Microsoft Azure and/or Microsoft Fabric.
• Proven experience designing and delivering production-grade data pipelines and Lakehouse/Warehouse solutions on the Microsoft data stack.
• Strong proficiency in SQL and Python (PySpark) for data engineering at enterprise scale.
• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline.
• Experience applying data privacy and compliance requirements such as GDPR, PII handling, and Microsoft data handling standards.
• Strong English written and verbal communication skills.
• Experience working within enterprise environments supporting global business and technical stakeholders.
• Demonstrated experience mentoring engineers and leading technical delivery.
• Ability to work independently while collaborating effectively across diverse technical and business teams.