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CapTech seeks a Data Engineer to develop data pipelines, advise clients on cloud technologies, and collaborate on data architecture solutions while leveraging AWS, Azure, or GCP.

The Senior Data Architect will develop data strategies, implement modern data architectures and lead teams in enhancing data management and delivery processes, aligning with business goals.

The Lead Data Strategist will enhance business development and client solutions using data expertise, managing teams, and advocating data technologies.

Full-Stack Engineers at CapTech design, develop, and maintain applications, collaborate with clients, and utilize modern web technologies in a consulting environment.

The Full-Stack Engineer at CapTech designs and develops enterprise systems, focusing on client-specific solutions and mentoring while utilizing a wide technology stack.

The Machine Learning Engineer designs and implements data-driven solutions, develops scalable ML systems, analyzes datasets, and leads client collaborations.

The Senior Technical Business Systems Analyst collaborates with business and technical stakeholders to elicit and design solutions, ensuring they meet business needs through data analysis, process evaluation, and effective communication.

Design and recommend end-to-end data architectures to meet client business goals. Assess and advocate data management technologies, improve data integration, quality, and delivery, evaluate architectural tradeoffs, mentor staff, collaborate with stakeholders, drive thought leadership, and support business development efforts.

Lead data architecture strategy and delivery for clients: assess current state, design modern cloud and hybrid data platforms, guide ingestion/storage/modeling, enforce governance, lead data engineering teams, present recommendations to executives, and grow practice capabilities and talent.

Lead design and delivery of end-to-end, production-scale ML systems on cloud platforms. Provide technical leadership, mentor teams, analyze and transform large datasets, implement recommender/NLP/risk models, productionize scalable ML, and grow practice through client-facing activities and business development.