Job Details

Senior Data Engineer – Reporting

Azure Data Engineer will play a key role in designing, developing, and optimizing data models, metrics, and reports that drive data-informed decision-making across the organization. This role combines strong Power BI visualization expertise with advanced data engineering skills in Databricks, ensuring high-quality, scalable data products for both enterprise reporting and self-service analytics use cases.

Key Responsibilities:

Design, develop, and maintain interactive Power BI dashboards and reports for various business domains (finance, operations, marketing, etc.).
Power BI/Fabric Reporting & Visualization
Leverage Microsoft Fabric for end-to-end data architecture – integrating Lakehouse, Data Flows, and Direct Lake models to power advanced Power BI analytics.
Create semantic models and DAX measures that are intuitive and optimized for performance.
Collaborate with business users to translate requirements into visual insights and define KPI frameworks.
Implement row-level security (RLS) and governance standards within Power BI workspace environments.
Support self-service BI adoption by developing certified datasets and user-friendly data models.

Databricks & Data Engineering

Design and build data pipelines and curated layers (Bronze, Silver, Gold) within Databricks using PySpark / SQL / Delta Lake.
Develop metric layers and data marts in Databricks to support Power BI and other analytical tools.
Ensure data quality, consistency, and accuracy through robust data validation and monitoring processes.
Implement performance tuning and cost optimization best practices for Databricks jobs and clusters.
Collaborate with the data governance and architecture teams to align data models with enterprise standards.

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Partner with business analysts, product owners, and stakeholders to identify new reporting opportunities.
Work closely with data governance, QA, and DevOps teams to ensure compliant, secure, and automated delivery.
Provide technical leadership and mentorship to junior engineers on best practices for BI and data engineering.

Support the development of metadata-driven frameworks and data catalogs to enable discoverability and reusability.

Requirements:

Experience with Power BI, Databricks, Azure, and DAX.
Proficiency in building interactive dashboards and reports.
Strong data engineering skills with Databricks and PySpark.
Knowledge of data governance and best practices for data validation.
Ability to collaborate with cross-functional teams and provide technical leadership.

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