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Cushman & Wakefield
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Sr. Azure Data Engineer

Sr. Azure Data Engineer

Cushman & Wakefield

4 - 6 years

5 - 9 Lacs

hyderabad

Posted:1 day ago| Platform:

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Skills Required

python pyspark data architecture sql data transformation continuous integration profisee performance tuning metadata management azure synapse ci/cd power bi azure data factory data engineering azure devops data bricks git spark devops dax etl

Work Mode

Work from Office

Job Type

Full Time

Job Description

Job Description Summary

Cushman & Wakefield is seeking a motivated Azure Data Engineer to join the Data Engineering & Analytics team. In this early-career role, you will support the design, development, and optimization of data pipelines on Azure to drive key business initiatives. Working under the guidance of senior engineers and architects, youll gain hands-on experience with modern data tools while contributing to high-impact, enterprise-scale projects. This is an excellent opportunity for professionals eager to grow their skills in a collaborative, client-centric environment that values innovation and data-driven decision-making.

Job Description

About The Role:

Design, develop, and manage scalable cloud-based data engineering solutions, including the implementation and optimization of ETL/ELT pipelines.
Lead the development of data pipelines and reusable frameworks in Python, PySpark, and SQL for batch and streaming use cases.
Collaborate with architects and engineering leadership to align technical implementations with business goals and innovation roadmaps.
Partner with governance and MDM teams to implement standards for data quality, metadata, lineage, and compliance using tools like Azure Purview and Profisee.
Support the integration of AI/ML workflows by preparing data for modeling, including feature engineering and deployment support.
Participate in design reviews, architecture discussions, and code assessments to ensure performance, resiliency, and scalability.
Mentor junior data engineers, conduct code reviews, and promote best practices in engineering and documentation.
Work closely with business analysts and data scientists to ensure data accessibility for analytics and reporting needs.
Contribute to the evaluation and adoption of emerging technologies in data ecosystems, streaming platforms, and DevOps tooling.
Implement and support DevOps practices including CI/CD pipelines, Git-based workflows, and automated testing environments.

About You:

Bachelors or Masters degree in Computer Science, Information Systems, or a related field.
4-6 years of hands-on experience in data engineering, preferably within cloud-native enterprise environments.
Proven expertise of at least one Azure data platform such as Azure Synapse Analytics, Azure Data Factory, Databricks, and Microsoft Fabric.
Advanced proficiency in SQL, Python, and PySpark for data transformation, performance tuning, and automation.
Strong understanding of cloud data architectures, including data lakehouse models, dimensional modeling (star/snowflake schemas), and event-driven pipelines.
Experience implementing data quality frameworks, metadata management, and lineage tracking using tools such as Azure Purview or Profisee.
Familiarity with DevOps practices, including CI/CD pipelines, Git workflows, and Azure DevOps.
Hands-on experience with Microsoft Fabric and Unity Catalog.
Knowledge of Spark Structured Streaming and near real-time data processing techniques.
Familiarity with Power BI, DAX, and dimensional data modeling concepts.
Experience integrating with data governance and MDM platforms such as Profisee, Azure Purview, or equivalent technologies.
Experience with test-driven development and database lifecycle management tools
Relevant certifications in Azure Data Engineering (e.g., DP-203) or cloud architecture (e.g., Azure Solutions Architect).

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Sr. Azure Data Engineer