Data Architect

Data Architect - Las Vegas, NV - Day1 onsite role Description for Internal Candidates Leverage modern data management toolsets and coding methods to design, build, implement, and optimize data solutions of all types - including support for OLTP and API/Microservices, data warehouses, data lakes, ODS, streaming data, analytic and BI/visualizations, etc. Transform legacy data structures and processes to modern, capable, and secure solutions in a hybrid cloud setup Apply Data Engineering & Design best practices to architect solutions, using a deep understanding of various data formats and database design approaches Design and Implement Data Services (DaaS) for consumption and various manipulations throughout the Data Ecosystem applying the "contract first" design principle and including the use of API, Microservices, Micro batch, ELT Pipeline, and other methods. Build best practices, drive data ingestion, and develop tooling for increasing scale, accuracy, and automation in the data pipeline, to integrate with decisioning, AI/NLP, and consuming systems Ensure data security by designing controls and protection strategies Enable application performance and modernization by creating appropriate data capabilities to match Position Requirements 8 years of experience in data engineering, development, and operations roles, including experience with transformational efforts. Strong Database skills, with RDBMS (E.g., Oracle, SQL) as well as modern relational and unstructured data sources (like NoSQL), including cloud services (AWS/GCP/Azure). Hands-on experience using tools is strongly preferred Experience with Tools (or similar) such as Hive, Airflow, Kafka, PostgreSQL, Oracle, SQL Server, Elasticsearch (ELK), JSON, Parquet, Avro, and other Data Storage formats, Tableau, Superset and other Visualization Tools, Apache Atlas, and other Data-centric Apache Packages Knowledge of Design Patterns for Software and Data Engineering. Experience Coding with Java, JavaScript (Nodejs), and Python. Experience in on-prem and hybrid cloud infrastructure, including service and cost optimization Experience with production and analytics data, batch, and real-time / streaming, etc. Experience with CI/ CD tools like Gitlab and Gitlab flow. Experience with OpenShift, Kubernetes, and Docker.