Data Engineer

Description

• Implement, troubleshoot and maintain the data engineering tools and environments that are necessary for the team's success — ETL tools, documentation/collaboration platforms, servers, etc.
• Building data warehouses, data lakes and other data stores for analytics
• Validate data quality by implementing data validation checks and monitoring data anomalies.
• Document ETL/ELT processes and data lineage.
• Assist in documenting technical specifications, data catalogs, and process workflows.
• Monitor and troubleshoot pipeline issues, ensuring data consistency and accuracy.
• Optimize data pipelines for performance, scalability, and reliability.
• Administer change management policies and procedures and conduct tabletop exercises to assess ETL process effectiveness.
• Work closely with data analysts and business stakeholders to understand data requirements and ensure accurate data delivery.
• Assist in data model design and schema creation.
• Communicate effectively with other teams across the organization, including technical & business teams.
• Stay up to date with industry trends, best practices, and emerging technologies related to data engineering.
• Perform maintenance on databases and other data stores, such as backups, indexing, and query optimization.
• Collaborate with the team lead to design and implement data pipelines that extract, transform (ETL) and load data from various sources into the data warehouse.
• Participate in training sessions and workshops to enhance your technical skills.

Requirements

• Technical documentation, especially around data; proficiency with related tools such as Confluence
• Eagerness to learn and grow in a dynamic data engineering environment
• Cloud solution technologies such as Azure or AWS, and their products
• Proficiency with Microsoft office tools including Word, Excel, Outlook
• Experience with SQL and relational databases (e.g., PostgreSQL or MySQL)
• Required: bachelor’s degree in Computer Science, Data Science, Business Analytics, Information Systems, or equivalent technical degree
• Strong attention to detail
• Data pipelining/ETL tools, especially those in Microsoft Fabric
• Business intelligence/reporting; proficiency with related tools, especially Power BI
• Experience using task management tools such as Jira or Microsoft Planner
• Conceptual data modeling for an organization, master data management, data quality testing, and/or other data governance processes and methods; proficiency with related tools such as Microsoft Purview
• Communicating with all corporate functions and understanding diverse data needs
• 2+ years in a professional business data engineering role (5+ to be considered for a Senior Data Engineer position)
• Excellent verbal and written communication skills
• Dimensional data modeling and schema design

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance