Chief Data Architect
hace 5 días
Dynatrace exists to make software work perfectly. Our platform combines broad and deep observability and continuous runtime application security with advanced AIOps to provide answers and intelligent automation from data. This enables innovators to modernize and automate cloud operations, deliver software faster and more securely, and ensure flawless digital experiences.
Salary & BenefitsWe offer a competitive salary range of $180,000 - $250,000 per year, depending on experience. In addition to your base salary, you will also receive a comprehensive benefits package, including health insurance, retirement savings plan, and paid time off.
About the RoleJob Description: We are seeking a Chief Data Architect to provide key technical direction for and hands-on effort with a small team of data engineers supporting our Business Intelligence function. A core role will be directing and helping to implement transformative pipelines of business data into our Snowflake environment.
Key Responsibilities:
- Lead the design, implementation, and maintenance of scalable data pipelines in the Snowflake ecosystem, including third-party vendor tools such as AWS, Fivetran, etc.
- Contribute to a Data Engineering strategy to ensure efficient data management for operations and enterprise analytics.
- Serve as a key technical expert for business stakeholder engagement on business data initiatives.
- Collaborate with colleagues in Data Modeling, BI, and Data Governance teams for platform initiatives.
- Provide the technical interface to data engineering vendors.
- Evaluate and recommend new data technologies and tools to improve data engineering processes and outcomes.
Qualifications:
- Significant experience in a hands-on data engineering role, especially in relation to business operations data.
- Bachelor's degree in Computer Science, Information Systems, or related field, or equivalent experience.
- Experience managing stakeholder engagement, collaborating across teams, and working on multiple simultaneous projects.
- Hands-on experience implementing robust, scalable data pipelines.
- Extensive experience acquiring data from REST APIs.
- Strong background in Python/Spark programming, with the ability to write efficient, maintainable, and scalable data pipeline code.
- Solid understanding of data warehousing, data lakes, MPP data platforms, and data processing frameworks.
- Strong understanding of database technologies, including SQL and NoSQL databases.
- Experience with CI/CD pipelines and DevOps practices for data engineering.
- Excellent problem-solving and analytical skills.
- Snowflake certification or other relevant data engineering certification is a plus.
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