Data Engineer

We are seeking a technically skilled and experienced Data Engineer to provide support and enhancement of our Enterprise Data Warehouse. The role focuses on modernizing ETL processes within an on-premises Cloudera Data Platform (CDP) environment, leveraging technologies like Apache Spark, Apache Iceberg, and Apache Airflow for scalable, efficient, and reliable data transformation and management. The ideal candidate will have strong ETL development and troubleshooting skills, along with experience participating in production support environments.

Essential job functions:

1. Development
• Contribute development efforts for ETL pipelines in the Enterprise Data Warehouse (EDW)
• Support and rebuild legacy ETL jobs (currently not using ACID transactions) with modern solutions using Apache Spark and Apache Iceberg to support ACID transactions.
• Transform and integrate EBCDIC Mainframe data into Hive and Impala tables using Precisely Connect for Big Data.
• Optimize data transformation processes for performance, scalability, and reliability.
• Ensure data consistency, accuracy, and quality across the ETL pipelines.
• Utilizes best practices for ETL code development, version control, and deployment using Azure DevOps.
2. Production Support
• Shares weekly 24/7 production support with managed service vendor on a 4-week rotation.
• Monitor ETL workflows and troubleshoot issues to ensure smooth production operations.
• Research and resolve user requests and issues
3. Collaboration and Stakeholder Engagement
• Collaborate with cross-functional teams, including data engineers, business analysts, administrators, and quality analyst engineers to ensure alignment on requirements and deliverables.
• Engage with business stakeholders to understand data requirements and translate them into scalable technical solutions.
4. Technical Governance
• Contribute to process documentation, and follow best practices within the Enterprise Data Warehouse
• Follow proper SDLC protocols within Azure DevOps code repository
• Stay updated on emerging technologies and trends to continuously improve data platform capabilities.
• Other tasks as assigned by management

Minimum Requirements:

• Bachelor’s degree in IT or similar field. (Additional equivalent experience above the required minimum may be substituted for the degree requirement.)
• 3+ years of experience in ETL development and data engineering roles
• 3+ years of advanced SQL experience
• 3+ years in Python or Linux for Spark-based development.
• Proven experience in using Apache Spark or Apache Iceberg or Airflow for ETL pipelines.
• Strong familiarity with version control systems, especially Azure DevOps.
• Knowledge of data governance and security best practices in a distributed data environment.
• Familiarity with data modeling, schema design, and building data models for reporting needs.
• In-depth understanding of ETL frameworks, ACID transactions, change data capture, and distributed computing.
• Experience in designing and managing large-scale data pipelines and workflows.
• Excellent problem-solving and troubleshooting skills.
• Effective communication and collaboration abilities to collaborate with diverse teams and stakeholders.
• Timeline centric mindset
• Enterprise application awareness and technical alignment standards
• This position requires (6C) personnel security screening in accordance with the U.S. Department of Education’s (ED) policy regarding the personnel security screening requirements for all contractor and subcontractor employees. A qualified applicant must successfully submit for personnel security screening within 14 calendar days from employment offer.

Preferred Qualifications:

• Experience with Cloudera Data Platform (CDP), including Hive and Impala
• Knowledge of Precisely Connect for Big Data or similar tools for mainframe data transformation