Golang Job: Sr. Data Software Architect

**Need 7+ years as a data architect and embedded product or automotive experience**

Job Description

This role focuses on enhancing the efficiency and automation of data pipelines, targeting innovative approaches to collect customer data. You will design and architect scalable and reliable data processing workflows, collaborate with data scientists and engineers, and optimize data pipelines for performance and efficiency.

Responsibilities

• Design and architect scalable data pipelines to automate data processing workflows
• Develop and test software to implement prototype code to validate designs
• Collaborate with data scientists, engineers, and stakeholders to understand data needs
• Develop and implement ETL processes for data transformation and loading
• Optimize data pipelines for enhanced performance, scalability, and efficiency
• Join a team responsible for creating data architectural designs and best practices
• Transform business requirements into conceptual, logical, and physical data models
• Promote a data-driven culture of quality, collaboration, rapid delivery, and business impact
• Collaborate with Product Managers, Delivery leads, System Engineers, and Software Development teams during solution design
• Author, refine, and improve corporate data architecture standards, procedures, and metrics
• Communicate data architecture concepts to both business and development teams
• Integrate Data Architecture with existing software delivery deployment processes

Essential Skills

• 7+ years of experience with Data Modeling, Data Warehousing, and working with large-scale datasets.
• Work with Business Architects, System Architects, Engineering, Data Architects, and/or Data Stewards to capture business requirements in a Logical Data Model.
• Contribute to determining the appropriate data platform(s) for solutioning efforts.
• Evaluate physical data models to ensure they align to the corresponding logical data model designs.
• Expertise in data architecture best practices, relational data modeling, data warehouse/data mart concepts, including expertise in facts and dimensions, and real-world modeling scenarios.
• Experience in integrating Data Architecture with CI/CD processes.
• Comprehensive understanding of data lineage, data mapping, data security/confidentiality/privacy and related data standards.
• Deep knowledge of entity-relationship diagrams, normalization, abstraction, denormalization, dimensional modeling, and meta data modeling practices.
• Working knowledge of Relational Database Management Systems (RDBMS) and SQL.
• Strong collaboration skills with demonstrated experience driving conversations and influencing without authority on complex data design challenges.
• Demonstrated willingness and confidence to make decisions with limited knowledge while balancing best practices, schedule, and business needs.
• Proven performance communicating up, down, and across an entire organization, with the ability to model and communicate complex concepts in both written and verbal communication.
• Demonstrated ability to work with limited supervision, break down complex data architectural requirements, prioritize work and execute.

Additional Skills & Qualifications

• 5+ years of experience with Collibra or actively engaged in leveraging the metadata within Collibra or a similar metadata repository
• Working experience in AWS or exposure to other cloud technologies
• Working knowledge of or exposure to Data Engineering and the respective tools and technologies (e.g., Databricks, Data Lake concepts)
• Working Knowledge of or exposure to AWS services such as Lambda, RDS, ECS, DynamoDB, API Gateway, S3, etc
• Working Knowledge of rest API development or providing data architectural support during API development
• Experience implementing and/or leveraging Data Governance and Stewardship program capabilities
• Passionate, creative and have the desire to learn new complex technical areas
• Accountable, curious, and collaborative with an intense focus on quality
• Skilled in interpersonal communications and ability to communicate complex topics to non-technical audiences Experience working in an agile team environment
• Demonstrated ability to function in a fast paced, collaborative team environment that is distributed across time zones and locations

Work Environment

The work environment is dynamic and collaborative, focusing on enhancing data pipeline efficiency and automation. Technologies and tools such as AWS, Python, Golang, Docker, and Kubernetes are widely used. The role encourages a data-driven culture and requires active participation in solution design, leveraging cloud platforms, ETL tools, and a comprehensive understanding of data architecture.