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Metro location, generalist data engineer title, and broad cloud/Databricks skill requirements increase competition.
Core data engineering skills transfer across industries, but finance ERP integration increases domain specificity.
Explicit 2-3 year requirement plus mandatory Databricks, PySpark, cloud, and ERP integration skills.
Design, develop, and maintain automated, scalable data pipelines integrating systems like Workday, Salesforce, and centralized BI data warehouse.
Own monthly BAU processing of billing data across commercial regions through automated workflows.
Serve as technical SME in data engineering, integration, and management, collaborating with cross-functional SME teams to ensure robust end-to-end data pipelines.
2-3 years of experience in data engineering and data integration, specifically building and managing cloud data pipelines (AWS, Azure, or GCP).
Proficient in PySpark (preferably Databricks), advanced SQL, Hadoop technologies including Hive and Spark.
Working knowledge of finance ERP suites and SaaS applications such as Workday, SAP, Salesforce.
Experience with SDLC practices, release and incident management tools like Bitbucket/GitHub and JIRA.
Experienced in managing finance-related data integrations and pipelines involving ERP and commercial business systems.
Strong stakeholder management skills working across technical and business units such as Finance, ERP, Billing, and Trading teams.
Detail-oriented with a focus on data modeling, transformation, data quality, and infrastructure optimization to support business-critical data flow and reporting.