Data Engineer
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Key Responsibilities:
Build and enhance scalable data pipelines using Azure Data Factory, Snowflake, and Azure Data Lake
Develop and maintain ELT processes to ingest and transform data from various structured and semi-structured sources
Write optimized and reusable SQL for complex data transformations in Snowflake
Collaborate closely with analytics teams to ensure clean, reliable data delivery
Monitor and troubleshoot pipeline performance, data quality, and reliability
Participate in code reviews and contribute to best practices around data engineering standards and governance
Qualifications:
5+ years of data engineering experience in enterprise environments
Deep hands-on experience with Snowflake, Azure Data Factory, Azure Blob/Data Lake, and SQL
Proficient in scripting for data workflows (Python or similar)
Strong grasp of data warehousing concepts and ELT development best practices
Experience with version control tools (e.g., Git) and CI/CD processes for data pipelines
Detail-oriented with strong problem-solving skills and the ability to work independently
Job ID: 145459303
Skills:
Metadata Management, Databricks, Python, Data lineage techniques, Master data management, Data modeling methodologies, Big Data storage architecture
Skills:
BigQuery, DataFlow, Python, Sql, API scripting, Airflow, Composer DAGs, Google Cloud SDK
Skills:
Oracle Cloud, RDBMS, Power Bi, Tableau, Workday, Sql, Salesforce
Skills:
snowflake , S3, Redshift, Jenkins, Lambda, Spark Streaming, Apache Kafka, Gitlab, Data Governance, Python, AWS, Alation, Glue, Data Quality Mesh
Skills:
.NET, data warehouses , Spark SQL, Power Bi, Azure Log Analytics, Powershell Scripting, Hive, Azure Data Factory, Data lakes, Microsoft Azure Data platform, Azure SQL Data Warehouse, Azure Storage Services, Azure Application Insights, Data Bricks, Stream Analytics, data marts, Event Hubs, Azure SQL DB, Azure Analysis Services
