Full-Time Lead Data Architect (AWS, Azure, GCP)

CapTech Data Architects match client business goals with available technologies for successful data delivery implementations. Enhancing data use, improving information stewardship, and streamlining data flows improve client business value.

Our architects gain in-depth understanding of client challenges, apply experience-based insights, and use cutting-edge tools & techniques to identify optimal solutions. Data Architects lead the Data & Analytics practice, growing talent and expanding delivery capabilities.

Specific Responsibilities:

• Assess and advocate data management technologies & practices, bridging current and future states.
• Interpret and deliver strategic plans, improving data integration, quality, and delivery supporting business initiatives.
• Formulate and articulate architectural trade-offs to recommend optimal solutions, ensuring technical requirements are met.
• Lead teams of data engineers and technical team members through design, implementation, and best practices.
• Provide insights to stakeholders and development teams to maximize client data value.
• Ensure recommended solutions provide business value and align with client strategies.
• Communicate with non-technical executives about the value of modern data solutions.
• Drive innovative technology solutions through thought leadership on emerging trends.
• Share project solutions and outcomes with colleagues to improve future projects.
• Partner with CapTech business development to demonstrate capabilities, envision solutions, and estimate work plans.

Typical Experience:

• 7+ years implementing various on-premises and cloud data management, integration, visualization, and analytical technologies.
• Advanced proficiency in modern data architectures, cloud services (AWS, Azure, GCP), real-time data distribution (Kafka, Kinesis), NoSQL databases (MongoDB, DynamoDB), and modern data warehouse tools (Snowflake, DataBricks).
• End-to-end data architecture solutions (ingestion, storage, relational modeling) leveraging industry standard languages (SQL, Python).
• Strategic thinking relating architectural decisions to business needs & client culture.
• Assessment of traditional and modern data components based on business needs.
• Recommendation of data governance best practices (MDM, security, privacy, policies).
• Leading enterprise engineering teams through implementations and serving as a point of contact on design decisions and best practices.

Preferred Qualifications:

• Previous consulting industry experience
• Providing thought leadership and internal engagement with leadership and innovation
• Mentorship and talent growth within the Data & Analytics practice
• Awareness and continued education around emerging data technologies.

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