Senior Staff Data Architect
1 week ago
Roles and Responsibilities
- Design and Architect Data Systems: Design and structure all data systems, including databases, warehouses, and lakes, focusing on security, scalability, and long-term strategy.
- Develop Data Models: Create and maintain logical and physical data models that translate complex business requirements into technical data specifications.
- Implement and Optimize Data Pipelines: Design, develop, and implement ETL/ELT processes, ensuring efficient and scalable data flow from various sources.
- Conduct Hands-on Code Reviews: Perform detailed code reviews for data-related projects, ensuring code quality, architectural integrity, and adherence to best practices.
- Oversee Self-Serve Data Platforms: Design, build, and oversee the creation of self-serve data platforms, empowering domain teams to manage their data products autonomously.
- Drive Data Governance and Quality: Define and enforce data governance standards, ensuring data quality, security, and compliance with regulations like HIPAA.
- Optimize Performance and Costs: Continuously mature and optimize the existing data architecture for better performance, cost-efficiency, and reusability.
- Evaluate and Recommend Technology: Research and recommend emerging data technologies and analytical methods to support the organization's needs and stay current with industry trends.
- Provide Technical Leadership: Offer expert guidance and mentorship to development teams, leading through technical challenges and promoting a culture of innovation.
- Communicate and Collaborate: Effectively translate technical strategies for non-technical stakeholders, align data solutions with business needs, and influence senior leadership.
Education Qualification
- Bachelor's Degree in Computer Science or "STEM" Majors (Science, Technology, Engineering and Math) with advanced experience.
- Candidates generally need 10+ years of professional experience in software development and data architecture.
- Extensive experience, often 4 or more years, with AWS or similar cloud technologies, particularly in designing scalable cloud solutions, is necessary.
- Strong hands-on experience with databases, big data technologies, and building reliable, large-scale data platforms is expected.
- Experience modernizing legacy data architectures for cloud and AI workloads is also valuable.
- Demonstrable experience with hands-on coding (Python, SQL, PySpark) for designing, implementing, and optimizing data architecture and pipelines.
- Proven experience in performing detailed code reviews and enforcing best practices in a data engineering context.
- Required technical skills include proficiency in Python and SQL, strong knowledge of relevant AWS services like MSK, EMR, Glue, Lambda, and Redshift, expertise in real-time data streaming with Kafka and Spark, and in-depth knowledge of data modeling, lineage, cataloguing, and metadata management.
- Essential soft skills include excellent communication, strong leadership, strategic thinking, and analytical problem-solving abilities. Familiarity with Agile development methodology is also beneficial.
- A master's degree in a relevant field like Computer Science or Information Systems is preferred.
- Additional technical knowledge in processing unstructured data using advanced techniques like multi-modal LLMs, experience with information retrieval or content management systems, and experience with multi-modal AI architectures are highly desirable.
- Specific industry experience, such as information security assessments for cloud products in the healthcare sector, is a plus.
- AWS certifications, especially the AWS Solution Architect certification, are preferred.
- The ability to consult with customers to align technical solutions with enterprise outcomes is also valued.
Relocation Assistance Provided: No
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