Data Engineer

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines using Azure Data Factory, Databricks, PySpark, and SQL
• Manage and integrate data across Azure (Synapse, Data Lake, Event Hub, Key Vault) and GCP (BigQuery, Cloud Storage)
• Develop workflows for data ingestion and processing via REST APIs and web services, including integrations with Salesforce and Oracle NetSuite
• Build and maintain data models, warehouses, and lakehouse structures to support analytics and reporting
• Optimize Spark jobs, SQL queries, and pipeline execution for scalability, performance, and cost-efficiency
• Ensure data privacy, security, and compliance while maintaining data lineage and cataloging practices
• Partner with business stakeholders, analysts, and PMO teams to deliver reliable data for operations
• Create and maintain technical documentation for data processes and pipeline workflows

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Analytics, Mathematics, Statistics, or IT
• 5+ years of experience in Data Engineering and large-scale data migration projects
• Proficiency in SQL, Python, and PySpark for data processing and transformation
• Hands-on expertise with Apache Spark, Databricks, and Azure Data Services (ADF, Synapse, Data Lake)
• Exposure to Google Cloud Platform (BigQuery, Cloud Storage) and multi-cloud data workflows
• Strong understanding of ETL/ELT development best practices and performance optimization
• Excellent problem-solving skills and the ability to work effectively in cross-functional teams

Preferred Qualifications

• Certifications in Azure or GCP cloud platforms
• Experience with API-based data ingestion tools such as Workato
• Knowledge of Oracle NetSuite, BambooHR, or Salesforce data ingestion processes

About the Company

Backbase is a leading engagement banking platform that helps financial institutions create seamless, personalized digital experiences for their customers.