Data EngineerOverall Purpose:The Data Engineer is a hands-on technical contributor accountable for the design, development, reliability, and continuous improvement of the organization's data engineering platforms and processes. This role combines deep technical execution with cross-functional collaboration, ensuring data pipelines, databases, and infrastructure are scalable, trusted, and aligned to business priorities. The Data Engineer upholds engineering standards, drives innovation within their domain, and takes ownership of data availability, quality, and performance across assigned systems and workflows.
Essential Functions:- Design, build, and operate data pipelines and databases that support analytics and reporting.
- Contribute directly to development while adhering to engineering standards and best practices.
- Develop and monitor data quality, availability, and performance across assigned data platforms and workflows.
- Continuously evaluate and recommend improvements to data engineering architecture, tools, and processes.
Knowledge, Skills and Abilities:- Strong knowledge of database technologies, data modeling techniques, and performance optimization, with hands-on proficiency in SQL for querying, transforming, and managing data across relational and analytical systems.
- Deep understanding of data engineering concepts, including data ingestion, transformation, orchestration, data modeling, and storage across modern data platforms, with practical experience building and maintaining ELT/ETL pipelines and data warehousing solutions.
- Proficiency in Python for data engineering tasks, including pipeline development, automation, and data transformation workflows.
- Experience working within cloud environments such as Microsoft Fabric, Azure or equivalent platforms, including deploying and maintaining data infrastructure and services.
- Experience following and contributing to engineering best practices, including version control, testing, CI/CD, and documentation.
- Working knowledge of data governance, security, and privacy principles as they apply to data engineering workflows and pipelines.
- High degree of ownership, accountability, and operational discipline in managing and delivering data engineering work.
Experience- 4+ years of progressive experience in data engineering, analytics engineering, or related technical roles.
- 4+ years of hands-on experience with SQL for data engineering, data modeling, transformation, and analytical workloads; Python experience a plus.
- 3+ years of hands-on experience in data modeling, ELT/ETL pipeline development, data warehousing, and data management, including Azure Data Factory for pipeline orchestration and data movement.
- 3+ years of cloud environment experience such as Azure - experience in Microsoft Fabric is a plus.
- Demonstrated experience contributing as a hands-on technical team member on data platform projects, including pipeline development, architecture participation, and code reviews.
- Experience following and contributing to data quality, monitoring, and reliability processes.
- Experience partnering with business, analytics, and product stakeholders to translate requirements into technical solutions.
Education- Bachelor's in Computer Science or a related field, or equivalent experience. Master's degree a plus.
Work Location & ScheduleThis role offers either a hybrid or fully remote work arrangement. Candidates within a 50-mile radius of a company office will follow our hybrid schedule, working on-site three days per week. Candidates located outside this radius will work remotely, with occasional travel to offices for meetings or key events.
Pay range: $135,000-165,000 depending on experience
