Azure Data Engineer
At a glance
Mid-level Data Engineering role at Sapsol Technologies Inc. Remote, United States · contract.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Create and support expandable data pipelines in Azure Data Factory and Databricks, using Spark
- Load and reshape records from Oracle and PostgreSQL, coordinating each step of their movement
- Clarify data needs with analysts, scientists and stakeholders, then supply data they can rely on
- Speed up Azure workflows and put data checks, lineage records and monitoring in place
- Review code, document processes, and contribute to governance, security and continued improvements
What you bring
- You need Microsoft Certified: Azure Data Engineer Associate or a more advanced credential
- You have practical experience with Azure Data Factory and Databricks, with PySpark or Scala preferred
- You can write effective SQL and work with Oracle and PostgreSQL
- You can build Azure ETL/ELT flows and orchestration, and have used Blob Storage or ADLS Gen2
Who this fits
This mid-level contract role suits someone able to work independently and alongside analysts, data scientists and other stakeholders. It is remote within the United States.
From the employer
Must Have: Certification: Required – Microsoft Certified: Azure Data Engineer Associate (or higher), Azure Data Factory,
Job Summary:
We are seeking a highly skilled Data Engineer with strong expertise in Azure Data Factory, Azure Databricks, Oracle, and PostgreSQL. The ideal candidate will design and implement robust data pipelines, optimize data flows, and contribute to our cloud data platform initiatives using the Microsoft Azure ecosystem.
Key Responsibilities:
- Design, build, and maintain scalable data pipelines using Azure Data Factory and Databricks (Spark-based).
- Ingest, transform, and orchestrate data from various sources including Oracle and PostgreSQL databases.
- Collaborate with data analysts, data scientists, and other stakeholders to understand data requirements and deliver clean, reliable data.
- Optimize performance of data workflows, especially within Azure environments.
- Implement data quality checks, lineage tracking, and monitoring processes.
- Follow and contribute to data governance, security, and compliance policies.
- Participate in code reviews, documentation, and continuous improvement initiatives.
Required Skills & Experience:
- Strong hands-on experience with Azure Data Factory and Azure Databricks (PySpark/Scala preferred).
- Solid working knowledge of Oracle and PostgreSQL databases, including writing efficient SQL queries.
- Proficient in building ETL/ELT workflows and data orchestration on Azure.
- Experience with Azure storage solutions (Blob Storage, ADLS Gen2).
- Strong understanding of data modeling, warehousing concepts, and performance optimization.
- Familiarity with CI/CD pipelines in Azure DevOps is a plus.
- Excellent problem-solving skills and ability to work independently or in a team.
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