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- Bachelorβs or Masterβs degree in Computer Science, Data Science, Engineering, or related field.
- 8+ years of experience in data engineering or data integration roles, with at least 3-5 years in a leadership capacity.
- Proven experience with modern data integration tools, ETL/ELT frameworks, and cloud data platforms.
- Experience with a wide variety of data sources, including EHRs and CRMs.
- 3-5 years of experience with data visualization tools such as Sigma or Looker.
- Deep understanding of data pipeline architectures, data modeling, and ETL best practices.
- Proficiency with SQL, Python, and familiarity with programming languages such as R.
- Experience with data quality management and monitoring tools.
- Familiarity with data governance principles and tools.
- Strong communication skills to convey technical concepts to non-technical stakeholders.
- Oversee the design, deployment, and maintenance of data pipelines and architecture for high-quality and timely data availability.
- Lead development and enforcement of data quality standards, governance, and monitoring practices.
- Act as primary liaison between data engineering and other departments to ensure data needs are met.
- Gather requirements, prioritize requests, and provide status updates on key projects to keep stakeholders informed.
- Develop and implement a strategic roadmap for data integrations in alignment with business goals.
- Assess current capabilities, identify areas for improvement, and ensure integration strategy scales with company growth.
- Manage and mentor a team of data engineers, fostering a culture of collaboration and continuous improvement.
- Contribute to the data engineering codebase, especially on high-impact projects, and ensure best practices are followed.
- Identify and evaluate new data sources for integration into the data ecosystem.
AWSPythonSQLETLData engineeringData visualizationData modeling
Posted 29 days ago
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