MS Fabric Data Engineer-INTL LATAM

Job Description

Insight Global is seeking an experience MS Fabric Data Engineer to build a modern data lake and analytics platform to empower investment teams with timely, reliable data to support portfolio construction, risk analysis, performance insights, and decision making. We are seeking someone with strong data engineering fundamentals, hands-on experience across Fabric services, and the ability to build scalable data models and pipelines supporting both analytics and Power BI reporting.

Key Responsibilities:

• Design and build data pipelines and transformations within Microsoft Fabric (Sematic model,

• Dataflows Gen1/2, Lakehouse, Direct Lake, Pipelines, Notebooks).

• Optimize Lakehouse performance through:

• Efficient table design (partitioning, V/Z-ordering, clustering)

• Managing file sizes, compaction, and vacuuming strategies

• Query tuning for Spark, SQL, and Fabric Warehouse engines

• Diagnose and resolve performance bottlenecks across ingestion, transformation, and serving layers.

• Implement monitoring and metrics around data latency, table performance, and pipeline throughput.

• Develop modular, reusable Python/PySpark code for data ingestion, validation, transformation, and automation.

• Build Python-based utilities for metadata management, orchestration helpers, and automated data quality checks.

• Implement medallion architecture (Bronze/Silver/Gold) to deliver clean, reliable, and analytics-ready datasets.

• Create standardized, well-modeled data tables to support analytics, reporting, and Power BI consumption.

• Partner with Power BI engineers to deliver trusted, high-performing datasets for reporting across investment, risk, and operations teams.

• Ensure alignment with DAX, Power Query, star-schema modeling, and best practices for incremental refresh and semantic modeling.

• Implement data quality checks, schema validation, and monitoring across the data lake.

• Leverage Fabric automation capabilities for scheduling, orchestration, and continuous operations.

• Contribute to metadata management, lineage tracking, access control, and data governance standards.

• Support CI/CD pipelines and source control practices for Fabric and Power BI assets.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

• 3+ years of hands-on experience with MS Fabric technology suites and Power BI

• Strong experience designing and supporting data Pipelines, Sematic models, Dataflows, and Lakehouse, Direct Lake, Notebooks and Gateway

• Performance tuning on Lakehouse and tools to monitor and troubleshoot

• Experience with Python and/or PySpark for data transformation and automation tasks.

• Proficiency with SQL, including building and tuning queries for large datasets.

• Solid understanding of medallion architecture and lakehouse principles.

• Working knowledge of Power BI data modeling, including DAX, M/Power Query, and semantic modeling best practices.

• Familiarity with data connectors (databases, APIs, OData) and cloud-based data environments (Azure preferred).

• Strong communication skills with the ability to collaborate with both technical and business users.