Role: Data Architect - AWS, CDP (Customer Data Platform), Databricks, GCP Full time Professional Remote - Nationwide About Onix: Onix is a leading cloud consulting company that helps customers get the most out of their technology with innovative, cloud-powered solutions and best-in-class services. We offer cloud solutions across a wide range of use cases and industries, from migration to advanced analytics and innovative AI solutions. With our global team of accomplished cloud experts, we are the most trusted cloud partner in the industry. Summary: Onix is seeking experienced Data Architects with a proven track record in production-level AWS data engineering implementations to join our delivery team. Ideal candidates will strongly understand Lakehouse Architecture, data modeling, and data management, focusing significantly on data streaming. We are seeking individuals with substantial experience in the AWS cloud platform, Customer Data Platform, streaming, and Databricks. Location: Remote - US, Support EST business hours Scope/Level of Decision-Making: This exempt position operates under limited decision-making and supervision. Position performs various assigned activities, referring more complex issues to the manager. Primary Responsibilities: Lead the design, development, and implementation of enterprise-level data engineering solutions, including, but not limited to, Lakehouse & data warehouse and other cloud-based data environments that integrate with an overall data architecture Provide thought leadership and technical expertise in designing, building, and optimizing end-to-end data pipelines, from data extraction and transformation to loading and visualization. Collaborate with business stakeholders, data engineers, data scientists, and other teams to understand data requirements, use cases, and business objectives. Design and implement efficient and robust data pipelines, ETL processes, and data integration workflows using AWS, Datanricks, and related technologies. Optimize and tune data processing frameworks, data ingestion mechanisms, and data storage strategies for performance and cost efficiency. Ensure data quality, integrity, and governance standards are met throughout the data engineering lifecycle. Create and maintain technical documentation, run books, code, and best practices for data and machine learning engineering on the AWS Stay up-to-date with the latest advancements in machine learning, Databricks, and MLOps, and propose innovative solutions to enhance our capabilities. Consult on Professional Services Engagements to help our customers design and implement data warehouse solutions. Lead and develop best practices for the larger data analytics delivery team. Provide client presentations to review project design, outcomes, and recommendations Preferred Qualifications & Skills . 5+ years or more consulting experience working with external clients across a variety of industry markets 7+ years experience in Data Architecture, data engineering & analytics in areas such as performance tuning, pipeline integration & infrastructure configuration In-depth knowledge of AWS data services and related technologies, including but not limited to: Redshift, Glue, S3, AuroraDB, MWAA, Lambda Deep knowledge and expertise in Databricks and its components, such as Unity Catalog, Delta Lake, Delta Live Tables, Apache Spark, and related technologies such as dbt. Production-level experience with data ingestion, streaming technologies (i.e., Kafka), performance tuning, trons utilizing programming languages such as Python, Spark, Java, or Scala 5+ years of experience building data pipelines using Big Data technologies, including Spark, Hadoop, or Cassandra Proficiency in programming languages such as Python or Scala, including