Data Engineering Lead
4 weeks ago
Maxonic is seeking a highly skilled Data Engineering Lead to join our team. As a key member of our organization, you will be responsible for designing, implementing, and optimizing our database architecture and data structures within our Salesforce and SAP ecosystem.
This is a 6-month contract opportunity located in Raleigh, NC, with a hybrid schedule, and potential to extend. The ideal candidate will have a solid understanding of database architecture and data integration processes and will be responsible for ensuring that our data structures and warehouses are aligned to support global reporting needs.
You will collaborate with various business and technical stakeholders like developers, architects, and analysts to deliver high-quality data solutions that support our organization's growth and operational efficiency.
A key component of this role will be to map, build, test, and maintain database pipeline architectures between Salesforce and SAP.
Key Responsibilities:- Participate in all phases of the Enterprise Data platform development life cycle as appropriate; including, but not limited to gathering customer requirements, defining technical requirements, creating high-level architecture diagrams, data validation, etc.
- Develop new data pipelines and ETL processes, while enhancing the efficiency of existing ones to support our global reporting objectives.
- Work closely with product managers, developers/architects, and business/reporting analysts to define/sign-off data requirements.
- Strong understanding of relational database concepts.
- Working knowledge of Salesforce Data/Object model.
- Some familiarity with cloud-based database solutions like Salesforce Data Cloud, AWS, Azure, Google, SAP DWC/DataSphere.
- Some familiarity with data visualization tools such as Tableau, SAC, Power BI.
- Ability to work closely with data analysts, and other stakeholders to translate business requirements into technical solutions.
- Experience in designing, building, and optimizing ETL/ELT data pipelines to process large datasets.
- Understanding of best practices for data modeling, including star schemas, snowflake schemas, and data normalization techniques.
- Strong documentation skills for pipeline design and data flow diagrams.
- Experience with Salesforce integrations, ETL processes, and data migration projects.
- Fundamental DevOps Practices, including knowledge of unit testing, CI/CD, and repository management.
- Some understanding of CAN-SPAM and GDPR and other data privacy regulations.
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