We are seeking a Data Engineer who is passionate about creating an excellent user experience and enjoys taking on new challenges. The Data Engineer will be responsible for the design, development, testing, deployment, and support of our Data Analytics and the Data warehouse platform.
Job Responsibilities:
Understand data services and analytics needs across the organization and work on the data warehouse and reporting infrastructure to empower them with accurate information for decision-making.
Develop and maintain a data warehouse that aggregates data from multiple content sources, including NoSQL DBs, RDBMS, Big Query, Salesforce, social media, other 3rd party web services (RESTful, JSON), flat-file stores, and application databases (OLTPs).
Use Python, Spark/PySpark, Data Bricks, Delta Lake, SQL Server, Mongo DB, Jira, Git/Bit Bucket, Confluence, Data Bricks/Delta Lake, REST services, Tableau, Unix/Linux shell scripting, and Azure Cloud for data ingestion, processing, transformations, warehousing, and reporting.
Develop scalable data pipelines using Data connectors, distributed processing transformations, schedulers, and data warehouse
Understanding of data structures, analytics, data modeling, and software architecture and applying this knowledge to problem solving.
Develop, modify, and test algorithms that can be used in scripts to store, locate, cleanse, verify, validate, and retrieve specific documents, data, and information
Develop analytics to understand product sales, marketing impact, and application usage for UWorld products and applications
Employ best practices for code sharing and development to ensure common code base abstraction across all applications. Continuously be up-to-date on industry standard practices in big data and analytics and adopt solutions to the UWorld data warehousing platform.
Work with QA engineers to ensure the quality and reliability of all reports, extracts, and dashboards by process of continuous improvement.
Collaborate with technical architects, developers, subject matter experts, QA team, and customer care team to drive new enhancements or fix bugs promptly.
Work in an agile environment such as Scrum
Minimum Experience:
Masters/bachelor s degree in computer science or a related field.
4 - 7 years of experience as a Data Engineer with experience in Data Analysis, ingestion, cleansing, validation, verification, and presentation (reports and dashboards)
4+ years of working knowledge and experience utilizing the following: Python, Spark/PySpark, Big Data Platforms (Data Bricks/Delta Lake), REST services, MS SQL Server/MySQL, MongoDB, and Azure Cloud.
Experience with SQL, PL/SQL, and Relational Databases (MS SQL Server/MySQL/Oracle). Experience with Tableau/Power BI, NoSQL (MongoDB), and Kafka is a plus.
Experience with REST API, Web Services, JSON, Build and Deployment pipelines (Maven, Ansible, Git), and Cloud environments (Azure, AWS, GCP) is desirable.
Soft Skills
Working proficiency and communication skills in verbal and written English
Excellent attention to detail and organization skills and ability to articulate ideas clearly and concisely
Ability to work effectively within a changing environment that is going through high growth
Exceptional follow-through, personal drive, and ability to understand direction and feedback
Positive attitude with a willingness to put aside ego for the sake of what is best for the team