Job description
Job Title: Data Platform Architect
Duration: 12 Months
Location: Washington, DC 20005
Job Overview:
We are seeking an experienced Data Platform Architect to guide the design and implementation of a scalable data solution for Databricks on AWS. The ideal candidate will have a strong background in data architecture, data integration, and data processing frameworks, with prior hands-on expertise in Databricks and a passion for optimizing diverse workloads.
Key Responsibilities:
- Design the data architecture for the platform and organizational use cases, focusing on scalability, performance, and support for advanced analytics and data science workloads.
- Ensure the platform supports multi-cloud operations, data sharing, and integration with various data sources, including on-premises and cloud environments.
- Ensure the platform integrates with various data delivery mechanisms including architecting data delivery mechanisms such as streaming, batch, and leveraging API's for encryption and decryption.
- Collaborate with Cloud Architects and Engineers to implement data governance, financial governance, and compliance features .
- Identify and architect automation approaches to simplify and accelerate CI/CD across multiple environments, onboarding of new users to the platform, creation of development workspaces, data quality enforcement, and integrated testing.
- Optimize the platform for handling diverse workloads, relational operations, and multi-model data processing.
- Develop and implement data ingestion and data processing frameworks, ensuring efficient and scalable data pipelines for common patterns.
- Architect and maintain data Lakehouse storage solutions, emphasizing best practices for data modeling and schema design.
- Provide guidance on best practices for data preparation exploration, and visualization within the platform.
- Lead client facing workshops and influence change and acceptance to modern data platform practices.
- Provide client-facing support, ensuring clear communication and understanding of technical solutions.
- Collaborate with stakeholders to document enterprise rollout strategies, data security blueprints, and architectural standards.
Qualifications:
- Degree in Computer Science, a technical field, or a related business field. Master degree preferred
- 3+ years of experience in designing and leading Databricks implementations
- 8+ years of experience in relevant technology roles, with a focus on data architecture.
- 5+ years in an advanced role, demonstrating leadership in guiding teams directly or indirectly.
- 5+ years of experience in architecting and maintaining big data platform architecture utilizing AWS Data & Analytics Services
- Strong Data Modeling experience
- Strong expertise in designing and supporting complex application architectures, including integration of disparate data sources.
- Experience in documenting enterprise rollout strategies and developing data security blueprints.
- Excellent communication skills
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Architect?
A: To succeed as a Data Architect, key technical skills include proficiency in data modeling, database design, and data warehousing, as well as expertise in data management tools such as ETL (Extract, Transform, Load) software and data governance platforms. Additionally, strong analytical and problem-solving skills, along with the ability to communicate complex technical concepts to non-technical stakeholders, are essential soft skills for this role. By combining these technical and soft skills, Data Architects can effectively design and implement data systems that support business growth and drive informed decision-making.
Q: What is the career path for a Data Architect?
A: A Data Architect's typical career progression involves starting as a Junior Data Architect or Data Analyst, where they develop foundational skills in data modeling, database design, and data warehousing. As they gain experience, they move into mid-level roles such as Senior Data Architect or Data Governance Lead, where they oversee data strategy, architecture, and compliance. Ultimately, senior Data Architects can transition into leadership positions like Chief Data Officer or Director of Data Engineering, where they drive organizational data vision and strategy.\n\nKey opportunities for skill development and professional growth in this role include learning cloud-based data platforms, advanced data modeling techniques, and data governance frameworks, as well as staying up-to-date with emerging technologies like artificial intelligence and machine learning. \n\nLong-term career prospects for Data Architects may include transitioning into leadership roles, pursuing specialized roles like Data Scientist or Business Analyst, or exploring adjacent fields like IT Consulting or Business Intelligence.
