Cloud Engineer
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Key Responsibilities
Design and maintain scalable ETL/ELT pipelines for batch and real-time data integration.
Develop optimized SQL queries, data models, and curated datasets for analytics.
Build data processing solutions using Python, PySpark, and distributed processing frameworks.
Implement solutions using Azure Data Factory, Databricks, Azure Data Lake, and Synapse or Microsoft Fabric.
Improve pipeline performance, reliability, data quality, and monitoring.
Implement DataOps practices and CI/CD pipelines using Azure DevOps.
Collaborate with analytics teams to provide trusted datasets for Power BI and other BI platforms.
Required Skills
6+ years of experience in data engineering, including hands-on cloud data platform experience.
Expert-level SQL and strong data modeling skills.
Strong proficiency in Python and PySpark.
Proven experience building and optimizing large-scale ETL/ELT pipelines.
Hands-on experience with Azure Data Factory, Databricks, and Azure Data Lake.
Experience with Azure Synapse Analytics or Microsoft Fabric.
Strong understanding of Apache Spark, distributed processing, and streaming technologies such as Kafka or Azure Event Hubs.
Experience with Git, Azure DevOps, CI/CD, and DataOps practices.
Understanding of Power BI data integration requirements, including preparing reporting-ready datasets.
Dashboard development is outside the scope of this role.
Nice to Have
Experience integrating data with Domo.
Exposure to Delta Lake, lakehouse architecture, and data governance.
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