5 or more years of hands-on experience as a Data Analyst or related technical engineering capacity.
Relevant technologies and programming languages include JAVA, Spring Boot, Python, IBM MQ, Oracle Database table design, queries and optimization.
Expertise in Database Design, Dimensional Modeling, and Data Warehousing.
Hands-on experience with Erwin Data Modeling Tool and metadata management.
2 or more years of proven experience in working with Data Lake and Teradata.
Proficiency in SQL for database querying, table creation, and data relationship management.
Experience engineering software within an Amazon Web Services (AWS) cloud infrastructure or other prominent enterprise cloud provider.
Demonstrable experience with DevOps principles, practices and tools.
Understanding of the full Software Development Lifecycle, building CI/CD pipelines and practicing Test Driven Development is a requirement.
Solid grasp of Agile Methodologies.
Experience with source control, build tools and GIT (GitHub, Bitbucket or other) is required.
High School diploma, GED or High School Equivalency.
Job Responsibilities:
Manage and transfer large data volumes via Data Lake and/or Teradata.
Design and implement database structures that support efficient data storage and retrieval.
Develop and maintain data models using Erwin Data Modeling Tool.
Perform dimensional modeling and ensure data warehouse optimization.
Write and optimize SQL queries (DMLs and DDLs) for querying databases, creating tables, and managing data relationships.
Fine-tune queries to enhance performance and manage complex data relationships.
Collaborate with cross-functional teams to meet AI/ML project requirements.
Design and develop data, and infrastructure solutions, seek opportunities to optimize performance, maintain and troubleshoot application components as required.
Design and develop with consideration for Non-Functional Requirements (Scalability, Reliability, Availability, Observability, Fault Tolerance).
Design solutions to meet functional and technical requirements.
Develop delivery pipelines and automated deployment scripts.
Configure services, such as databases and monitoring.
Assisting in the design, implementation and optimization of related approaches, tools and workflows.