Data Engg with DQ Exp

Fractal Analytics•California, CA

1d•$140,000 - $160,000

About The Position

We are seeking an experienced Azure Architect with strong expertise in Data Engineering and Data Quality (DQ) frameworks to design, implement, and govern scalable enterprise data platforms on Microsoft Azure. The ideal candidate will have deep experience in cloud-native data architectures, modern ETL/ELT pipelines, data governance, and enterprise-grade data quality practices. The role involves working closely with business stakeholders, data engineers, architects, analytics teams, and leadership to build reliable, secure, and high-performing data ecosystems.

Requirements

Azure Data Factory (ADF)
Azure Databricks
Azure Synapse Analytics
Azure Data Lake Storage (ADLS)
Azure SQL Database
Azure Purview / Microsoft Purview
Azure Event Hub / Stream Analytics
Azure Functions
Azure DevOps
Expertise in SQL and Python/PySpark.
Strong understanding of data modeling techniques.
Experience building distributed data processing systems.
Knowledge of batch and streaming architectures.
Experience with Delta Lake/Lakehouse concepts.
Experience implementing enterprise Data Quality frameworks.
Knowledge of DQ tools/frameworks such as Great Expectations, Deequ, Monte Carlo, Informatica DQ, or custom validation frameworks.
Experience in data profiling, validation, reconciliation, and anomaly detection.
Understanding of data governance and metadata management.
CI/CD implementation for data pipelines.
Infrastructure as Code (IaC) exposure using Terraform/Bicep/ARM templates.
Experience with monitoring and logging frameworks.
Understanding of cloud security best practices.
Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or related field.
8+ years of experience in Data Engineering and Cloud Architecture.
4+ years of hands-on experience with Azure Data Platform.
Experience working in enterprise-scale cloud transformation programs.
Strong communication and stakeholder management skills.
Excellent problem-solving and analytical thinking.
Ability to lead technical discussions and architecture reviews.
Strong collaboration and mentoring capabilities.
Ability to work in fast-paced and cross-functional environments.

Nice To Haves

Azure Solutions Architect Expert
Azure Data Engineer Associate
Azure AI Engineer (preferred)
Experience in BFSI, Healthcare, Retail, Manufacturing, or CPG domains.
Exposure to AI/ML data platforms.
Experience with multi-cloud or hybrid-cloud environments.
Familiarity with Agile delivery models.
Client-facing consulting experience.

Responsibilities

Design scalable and secure enterprise data platforms on Microsoft Azure.
Define end-to-end cloud data architecture using Azure-native services.
Develop reference architectures, reusable frameworks, and best practices.
Lead migration of on-premise data platforms to Azure cloud.
Ensure architecture aligns with business, security, governance, and compliance requirements.
Build and optimize large-scale batch and real-time data pipelines.
Design ETL/ELT frameworks using modern Azure data services.
Implement lakehouse/data warehouse architectures.
Enable data integration from structured, semi-structured, and unstructured sources.
Optimize performance, scalability, and cost of Azure data solutions.
Define enterprise data quality standards, controls, and monitoring frameworks.
Implement DQ checks including completeness, accuracy, consistency, uniqueness, and timeliness.
Design automated DQ validation and reconciliation frameworks.
Collaborate with governance teams on metadata management, lineage, and master data initiatives.
Establish data observability and monitoring mechanisms.
Work with business users to understand analytical and operational data requirements.
Collaborate with cross-functional teams including BI, AI/ML, governance, and infrastructure teams.
Mentor junior engineers and provide technical leadership.
Participate in architecture reviews, design discussions, and client presentations.