Senior Data Engineering Specialist

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever‑growing range of opportunities to discover what makes you thrive at every stage of your career.

Try new things, learn new skills and discover what you excel at—all from Day One.

Key Responsibilities:

• Guide team to migrate from on Prem Cloudera to Azure cloud environment.
• Designed and implemented scalable data lake solutions using Snowflake and Databricks, Developed and optimized data pipelines for ingestion, transformation, and storage.
• Managed data governance, quality, and security across cloud environments and Implemented performance tuning, automation, and CI/CD for data workflows.
• Collaborated with cross‑functional teams to support cloud migration activities.

• Install, configure, manage, and monitor Cloudera Hadoop clusters, ensuring high availability, performance, and security. This includes managing HDFS, YARN, and other ecosystem components.

• Tune Hadoop, Hive, and Spark jobs and configurations for optimal performance, efficiency, and resource utilization. This includes optimizing queries, managing partitions, and leveraging in‑memory capabilities.

• Diagnose and resolve issues related to Linux servers, networks, cluster health, job failures, and performance bottlenecks. Provide on‑call support and collaborate with other teams to ensure smooth operations.

• Implement and manage security measures within the Cloudera environment, including Kerberos, Apache Ranger, and Atlas, to ensure data governance and compliance.
• Setup and manage Hashi Corp Vault for secure keys and secrets management.
• Utilize Cyber Ark for privileged access management and secure administrative tasks on the cluster.

• Migrate Hadoop, Hive, and Spark data and applications to Azure cloud services such as Azure Synapse Analytics, Azure Databricks, or Snowflake. Ensure data integrity, performance tuning, and validation.
• Automation and Scripting:
  Develop scripts (e.g., shell, Ansible, Python) for automating administrative tasks, deployments, and monitoring. Work with users to develop, debug, optimize Hive/Spark/Python programs that connect to the Cloudera environment.

• Create and maintain documentation for system configurations, operational procedures, and troubleshooting knowledge bases.

• Work closely with the Cloudera vendor to stay current with the latest releases, perform upgrades, and address vulnerabilities.

• Advanced degree in Computer Science, Engineering, or related field.
• Deep expertise in Data Engineering and Management technologies, synthetic data, automation, advanced analytics.
• 10+ years of hands‑on experience in Data engineering, Cloud platform management, and performance optimization.
• Hands‑on experience with Hadoop, Hive, Spark, and migration of Big Data into Azure cloud services.
• Working knowledge and hands‑on experience in Data Integration and Data Lake Architectures with Databricks and Snowflake platforms.
• Working knowledge of Microsoft Azure cloud and big data migration to cloud platforms.
• Experience with Hashi Corp Vault for secrets and keys management.
• Experience with Cyber Ark for privileged access and administrative security tasks.
• Proficiency in Linux, clustering, and distributed systems.
• Expertise in Hive and Spark for data processing and analytics.
• Expertise in Hadoop ecosystem components such as HDFS, YARN, Hive, Spark, and Sqoop.
• Proficiency in languages such as shell, Ansible, C/C++, Java, and Python, Pyspark for automating workflows, deployments, and monitoring.
• Expertise in Linux, Network, Python scripting, DNS, Kerberos, LDAP/AD, MySQL, Postgre
  
  SQL, Jupyter Hub.
• Experience in creating and maintaining documentation for system configurations, operational…