Data Engineer

Our Team:
Enterprise Business Solutions

Vista's Enterprise Business Solutions (EBS) domain is working to make our company one of the most data-driven organizations to support Finance, Supply Chain, and HR functions. The cross-functional Data Lake Analytics team focuses on providing Vista with cutting-edge tools and access to SAP data insights we can use to make fast decisions and deliver customer value. EBS team members are empowered to learn new skills, communicate openly, and be active problem-solvers who bring proactivity, creativity, and curiosity to our daily engineering challenges.

Join our EBS Domain as a Data Engineer! This role will be responsible for building, operating, and supporting robust data pipelines and data warehousing solutions. The Data Engineer will implement industry best practices, data standards, and optimized ETL/ELT workflows under the guidance of experienced colleagues. This role has a lot of opportunities to impact general data pipeline development and the implementation of new solutions.

You will work on modernizing data technology solutions in EBS, including cloud warehousing, finance, and supply chain datasets. This role will require a solid understanding of cloud data integration tools and cloud data warehousing, with a strong ability to execute technical initiatives to tangible results.

As a Data Engineer, you will be instrumental in executing our data strategy, ensuring data quality, and contributing to the technical execution of our data products. Your responsibilities will include:

• 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.

• 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, Cloud Watch and Event Bridge 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.

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