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Data Engineer (ID: 3583)

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Job Description - Data Engineer (ID: 3583)

As a Data Engineer, you will:
  • Design, build, and maintain scalable data pipelines using Databricks, PySpark, and Azure Data Factory.
  • Develop and optimize data ingestion, transformation, and loading processes for structured and unstructured data sources.
  • Implement data governance frameworks to ensure proper data ownership, compliance, and security standards.
  • Build and maintain reliable data quality validation processes to ensure accuracy, consistency, and completeness of enterprise data.
  • Establish data lineage tracking mechanisms to provide transparency on how data flows across systems and pipelines.
  • Develop and maintain Python scripts and automation tools to streamline data engineering workflows.
  • Collaborate with data scientists, analysts, and business stakeholders to deliver high -quality datasets for analytics and AI initiatives.
  • Optimize data pipeline performance and scalability within Azure -based data platforms.
What You Bring to the Table:
  • 8+ years of experience in data engineering, data platform development, or big data environments.
  • Strong hands -on experience with Databricks and PySpark for distributed data processing.
  • Practical experience working with Azure Data Factory for orchestration and data pipeline development.
  • Advanced Python scripting skills for automation, transformation, and integration tasks.
  • Solid understanding of data governance principles, including metadata management, data cataloging, and compliance.
  • Experience implementing data quality frameworks and validation rules within data pipelines.
  • Hands -on experience with data lineage tracking and documentation practices.
  • Experience working with large -scale data processing frameworks and cloud -based data platforms.
You should possess the ability to:
  • Architect and implement end -to -end data pipelines that support large -scale data processing.
  • Design efficient data models and transformation logic using PySpark and Databricks.
  • Implement data governance and compliance practices within enterprise data ecosystems.
  • Identify and resolve data quality issues proactively through automated validation and monitoring.
  • Track and document data lineage across multiple data sources and transformation layers.
  • Write clean, scalable, and maintainable Python code for data engineering workflows.
  • Collaborate effectively with cross -functional teams including data scientists, analysts, and platform engineers.
  • Troubleshoot and optimize data pipeline performance, reliability, and cost efficiency in Azure environments.
What We Bring to the Table:
  • Opportunity to work on large -scale cloud data platforms and advanced data engineering solutions.
  • Exposure to modern data stack technologies including Databricks, Azure Data Factory, and distributed processing frameworks.
  • Collaborative environment working with data scientists, analytics teams, and engineering professionals.
  • Challenging projects focused on building scalable and enterprise -grade data platforms.
  • Opportunities to enhance expertise in data governance, data quality, and lineage frameworks
Let’s Connect

Want to discuss this opportunity in more detail? Feel free to reach out.

Recruiter: Aswin Dhanvandhar
Phone: +31 20 369 0609 ; Extn :141

Original job Data Engineer (ID: 3583) posted on GrabJobs ©. To flag any issues with this job please use the Report Job button on GrabJobs.
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