Senior Data Engineer
- Independently resolve a diverse range of complex data engineering problems where precedent may not exist.
- Apply sound judgment in evaluating and selecting methods to develop scalable data solutions.
- Design, build, and optimize data pipelines, architectures, and datasets to support business intelligence and advanced analytics.
- Create or significantly improve existing data solutions, processes, and tools to enhance data quality, reliability, and performance.
- Operate with minimal guidance on nearly all assignments; work is reviewed at critical milestones and upon completion.
- Serve as a mentor and technical resource for less experienced engineers.
- Collaborate with cross-functional teams including analytics, product, and engineering to deliver impactful data solutions.
- Represent the data engineering function in internal and external project discussions.
- Communicate complex technical concepts effectively to both technical and non-technical stakeholders.
- Influence practices and procedures within the department.
- Bachelor's degree with at least 5 years of experience, or equivalent.
- In-depth knowledge and expertise in data engineering, including:
- Snowflake (data warehousing and performance tuning)
- Informatica (ETL/ELT development and orchestration) - nice to have
- Python (data processing and scripting) - required
- AWS (data services such as S3, Glue, Redshift, Lambda) - required
- Cloud data practices and platform - AWS required
- Basic knowledge of related disciplines such as data science, software engineering, and business analytics.
- Proven ability to independently resolve complex problems and develop scalable data solutions.
- Strong communication skills, with the ability to effectively convey technical concepts to diverse audiences.
- Master's degree with at least 3 years of experience, or equivalent.
- Experience leading smaller projects or phases of larger initiatives.
- Familiarity with data governance and data quality best practices.
- Experience with advanced analytics and machine learning techniques.
- Strong analytics skillset, including experience working with analytical teams, interpreting business KPIs, and enabling data-driven insights.
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