Data Engineer III

This role is ideal for someone who enjoys building large-scale data solutions, developing robust data pipelines, and partnering with business and technical stakeholders to turn data into actionable insights. What You’ll Do

• Design, build, and maintain data platforms and data assets supporting analytics and data product initiatives
• Develop scalable data pipelines to ingest, transform, and load data in big data environments
• Build robust, testable solutions using Spark and other modern data engineering technologies
• Design and implement strategic and tactical data stores for enterprise data consumption
• Develop frameworks and microservices that deliver data products to internal consumers
• Partner with Data Scientists, Data Product teams, Data Management, and Engineering teams to deliver high-quality data solutions
• Ensure data quality, integrity, accessibility, and readiness for business use cases
• Translate business requirements into scalable data solutions and engineering designs
• Support automation and continuous improvement of enterprise data products
• Serve as a trusted advisor to business leaders by identifying opportunities to leverage data for strategic decision-making

• Bachelor’s degree in Business, Computer Science, Engineering, Information Systems, or a related field
• 8+ years of data engineering, data management, or analytics experience
• Experience building and supporting enterprise-scale data solutions
• Strong experience designing and developing relational data structures
• Experience integrating and transforming complex data from multiple sources
• Proven ability to deliver operational and analytics-focused data assets

Preferred Qualifications

• Financial services or banking industry experience
• Experience supporting large, highly regulated enterprise environments
• Background in Big Data Engineering and Advanced Analytics

Technical Skills

• Apache Spark
• Hadoop ecosystem technologies
• Airflow, Argo, Luigi, or similar orchestration tools
• CI/CD and DevOps practices
• Docker and Kubernetes
• NoSQL databases such as MongoDB, Cassandra, or HBase
• Streaming technologies including Kafka, Flink, or Spark Streaming
• Data modeling, data warehousing, and data architecture
• Business intelligence and reporting solutions, * Strong communicator who can work effectively with both technical and non-technical stakeholders
• Experience delivering scalable data products and data platforms
• Ability to translate business needs into technical data solutions
• Comfortable working with senior leadership and driving data-driven decision making
• Passion for building modern, enterprise-grade data ecosystems