Assistant Vice President; Data Engineer

Bank of America Bank of America · Banking · Charlotte, NC

This role focuses on developing and delivering complex data solutions, including integration, cleaning, transformation, and control of data in operational and analytical systems. It involves building data pipelines, deploying machine learning models on big data platforms, and ensuring data quality within a financial services context.

What you'd actually do

  1. Develop and deliver complex data solutions to accomplish technology and business goals.
  2. Code, design and deliver of tasks associated with the integration, cleaning, transformation, and control of data in operational and analytics data systems.
  3. Work with the stakeholders, Product Owners, and Software Engineers to aid in the implementation of data requirements, analyze performance, conduct research and troubleshoot any issues.
  4. Perform Proficient data engineering practices and have extensive experience of using design and architectural patterns.
  5. Define and build data pipelines that enable faster, better, data‐informed decision‐making within the business.

Skills

Required

  • Master's degree or equivalent in Computer Science, Computer Information System, Information Technology, Management Information Systems, Engineering (any), or related
  • 3 years of experience in the job offered or a related IT occupation
  • Utilizing Hadoop/Big Data and Scalable Distributed Systems to provide analytical insights using TeraBytes of data
  • Configuring and tuning of Hadoop services including Hive, Spark, HBase, HDFS, Impala, Kafka
  • Developing applications on container orchestration platform like Kubernetes and Docker to build dynamic and scalable applications
  • Designing solutions to deploy scalable machine learning models on big data platform
  • Developing batch and real time data pipelines to ingest data into Data Warehouse
  • Using Source Code Version Control systems and Jenkins to provide continuous and efficient delivery of data products

What the JD emphasized

  • Designing solutions to deploy scalable machine learning models on big data platform