Data Engineering

Qualifications

• 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