Data Engineer

Summary

Vista is the design and marketing partner to millions of small businesses around the world. They are seeking a Data Engineer to build, operate, and support data pipelines and warehousing solutions, ensuring data quality and contributing to technical execution of data products.

Responsibilities

• Design, build, and implement scalable, robust, and high-quality ETL/ELT processes to support growing business demand for information, delivering data as a reliable service
• Adhere to and enforce best practices for data quality, testing, data governance, and architecture within your daily deliverables
• Actively participate in the team’s use of Agile methodologies, ensuring smooth, predictable, and continuous delivery of data features
• Utilize cutting-edge approaches to data transfer, transformation, and cloud data warehousing to drive optimization in existing data pipelines
• Develop a profound understanding and 'feel' for the business meaning, lineage, and context of each data field within our domain (Finance and Supply Chain)
• Implement robust data processing methodologies, specifically focusing on incremental loading logic and Change Data Capture (CDC)
• Collaborate with senior engineers, functional SAP team members, and data consumers to understand requirements and successfully deliver data solutions
• Engage with data consumers to achieve a clear understanding of their specific data usage, pain points, and current gaps to resolve data issues collaboratively
• Produce clear, concise, and comprehensive documentation for code, workflows, and system architecture
• Grow into analytical and reporting responsibilities over time, actively participating in insight gathering rather than focusing solely on data pipeline implementation

Skills

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field
• 3-4 years of professional hands-on experience in Data Engineering
• Strong knowledge of SQL and core data warehousing concepts is a must
• Solid knowledge of Python for data processing and automation
• Solid understanding of Data Modeling concepts, specifically hands-on experience with Dimensional Modeling techniques
• Hands-on experience in managing scalable pipelines in cloud environments, with specific proficiency in AWS services like S3, EC2, IAM, CloudWatch and EventBridge etc
• Hands-on experience with cloud-based data warehousing platforms is critical (Snowflake preferred)
• Good understanding of data pipeline ingestion patterns, specifically incremental loading and Change Data Capture (CDC)
• Strong knowledge of production standards such as versioning (Git), CI/CD
• Good understanding of data quality frameworks and data validation approaches in modern data warehousing platforms
• Demonstrate experience or strong interest in analytical reporting and insight gathering (analytical mindset and interest is a must-have, but hands-on experience with reporting tools like Looker is not required)
• Problem-solving and multi-tasking ability in a fast-paced, globally distributed environment
• Familiarity with data visualization and reporting tools (experience with Looker and LookML skills is a plus)
• Familiarity with extracting and processing SAP ERP data (experience with tools like Theobald Xtract Universal is a major plus)
• Knowledge of finance, accounting, supply chain, logistics, operations, or procurement data
• Experience managing work in Jira and writing technical documentation in Confluence

Qualifications

Must Haves

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field
• 3-4 years of professional hands-on experience in Data Engineering
• Strong knowledge of SQL and core data warehousing concepts is a must
• Solid knowledge of Python for data processing and automation
• Solid understanding of Data Modeling concepts, specifically hands-on experience with Dimensional Modeling techniques
• Hands-on experience in managing scalable pipelines in cloud environments, with specific proficiency in AWS services like S3, EC2, IAM, CloudWatch and EventBridge etc
• Hands-on experience with cloud-based data warehousing platforms is critical (Snowflake preferred)
• Good understanding of data pipeline ingestion patterns, specifically incremental loading and Change Data Capture (CDC)
• Strong knowledge of production standards such as versioning (Git), CI/CD
• Good understanding of data quality frameworks and data validation approaches in modern data warehousing platforms
• Demonstrate experience or strong interest in analytical reporting and insight gathering (analytical mindset and interest is a must-have, but hands-on experience with reporting tools like Looker is not required)
• Problem-solving and multi-tasking ability in a fast-paced, globally distributed environment

Nice to Haves

• Familiarity with data visualization and reporting tools (experience with Looker and LookML skills is a plus)
• Familiarity with extracting and processing SAP ERP data (experience with tools like Theobald Xtract Universal is a major plus)
• Knowledge of finance, accounting, supply chain, logistics, operations, or procurement data
• Experience managing work in Jira and writing technical documentation in Confluence

Benefits

• Award winning Remote-First company