9+ years of overall technology experience that includes at least 3+ years of hands-on software development, data engineering, and systems architecture.
3+ years of experience with Salesforce Cloud Technologies is must.
3+ years of experience with Sales force Customer data modeling, data warehousing, and building high-volume ETL/ELT pipelines.
3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
3+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala etc.).
2+ years in cloud data engineering experience in Azure.
Fluent with Azure cloud services. Azure Certification is a plus.
Experience with integration of multi cloud services with on-premises technologies.
Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines.
Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations.
Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
Experience with at least one MPP database technology such as Redshift, Synapse or SnowFlake.
Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes.
Experience with version control systems like Github and deployment & CI tools.
Experience with Azure Data Factory, Azure Databricks and Azure Machine learning tools is a plus.
Experience with Statistical/ML techniques is a plus.
Experience with building solutions in the retail or in the supply chain space is a plus
Understanding of metadata management, data lineage, and data glossaries is a plus.
Working knowledge of agile development, including DevOps and DataOps concepts.
Familiarity with business intelligence tools (such as PowerBI).
BA/BS in Computer Science, Math, Physics, or other technical fields
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