Data Engineer
Responsibilities:
• Lead the development of enterprise data pipelines and modeling solutions that enable reliable reporting, analytics, and operational decision-making.
• Provide day-to-day technical direction for a small team of data engineers, offering mentorship, code guidance, and support for delivery priorities.
• Design, build, and optimize ETL workflows using Python and SQL to move and transform data from a wide range of upstream systems.
• Create and maintain scalable data structures in Snowflake and Databricks to support performance, usability, and long-term maintainability.
• Establish engineering standards, documentation practices, and development approaches that improve consistency and quality across data initiatives.
• Collaborate with business and technical stakeholders to translate data needs into practical architecture and implementation plans.
• Contribute directly to hands-on coding, testing, troubleshooting, and deployment activities across the data engineering lifecycle.
• Evaluate data quality, resolve integration challenges, and improve pipeline reliability through monitoring and continuous enhancement.
Qualifications:
• Demonstrated experience in data engineering with a strong background in designing and implementing ETL solutions.• Proficiency in Python and SQL for data transformation, automation, and performance tuning.
• Hands-on experience with Snowflake and Databricks in production data environments.
• Familiarity with Microsoft Fabric and its use in modern data platform ecosystems.
• Proven ability to integrate data from multiple source systems and consolidate it into scalable data models.
• Experience leading technical workstreams or mentoring entry-level engineers within a small team setting.
• Strong understanding of data architecture, pipeline optimization, and engineering best practices.
Compensation
$140,000.00-$150,000.00 YearlyAbout Us
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