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Mid-level data engineer role, broad generalist tech stack and metro hiring increases candidate density.
Core data engineering skills transferable, but CRM and marketing integrations raise domain specificity.
Specific 3+ year experience and mandatory Azure, Databricks, Salesforce, GA4, and Python skills.
Design and implement scalable ETL/ELT data pipelines using Azure Data Factory, Databricks, and Synapse Analytics to support data warehouse and data lake operations.
Develop and manage data warehouse architecture including data modeling, transformation logic, and schema design to enable business insights via dashboards and reports.
Collaborate with BI analysts, data scientists, and application teams to deliver end-to-end data solutions with emphasis on data quality, compliance, and traceability.
Minimum 3+ years of analytics/data engineering experience with at least 2 years in architecting and solutioning data platforms.
Expert-level skills in Azure Data Factory, Azure Databricks, Synapse Analytics, advanced SQL/T-SQL, and Python programming.
Experience integrating data from Salesforce CRM, Pardot, and Google Analytics (GA4) into data warehouses using APIs or connectors.
Mandatory skills: SQL, Python, Pardot Data Pipelines, Google Analytics, Salesforce Integration.
Experienced in architecting and implementing complex data pipelines involving marketing automation and CRM data sources.
Proficient in cloud-based Microsoft Azure data technologies with hands-on skills in automation, CI/CD, and scripting.
Comfortable translating business requirements into scalable, secure, and governed data solutions supporting analytics and ML workloads.