Jr. Data Engineer

MOHELA

About The Position

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

Requirements

Bachelor’s degree in IT or similar field. (Additional equivalent experience above the required minimum may be substituted for the degree requirement.)
Basic SQL experience
Basic Python and general SDLC best practices.
Basic Linux operations skills.
Familiarity with version control systems
Familiarity with data modeling, schema design, and building data models for reporting needs.
Understanding of ETL frameworks, ACID transactions, change data capture, and distributed computing.
Effective communication and collaboration abilities to collaborate with diverse teams and stakeholders.
Timeline centric mindset
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.

Nice To Haves

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

Responsibilities

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.
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
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.
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