Solution Architect

Accountabilities As Solution Architect, you will provide technical direction throughout the design and delivery of enterprise data and AI solutions. You will work closely with clients and internal teams to develop scalable architectures, address complex engineering challenges, and ensure that technical solutions align with business objectives.

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Develop forward-looking data strategies aligned with client business goals, technical requirements, and industry best practices.

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Design and oversee large-scale AI, data lakehouse, and data warehouse implementations using Databricks and other cloud-native technologies.

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Architect integrated data solutions across on-premises infrastructure and multiple cloud environments.

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Design and implement batch and streaming data ingestion, real-time processing, and ETL/ELT pipelines.

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Define data models, integration specifications, infrastructure configurations, security policies, and access controls.

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Ensure data quality, privacy, security, and regulatory compliance across client implementations.

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Identify and resolve complex data engineering challenges while making technical decisions that minimize delivery risks.

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Drive performance optimization, cost efficiency, scalability, and maintainability across data platforms and pipelines.

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Evaluate and introduce emerging technologies, frameworks, and methodologies to continuously improve client solutions.

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Create technical blueprints and recommend appropriate tools, architectures, and design patterns based on client requirements.

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Lead technical discovery sessions and translate business needs into solution architectures.

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Support presales activities by developing technical proposals, responding to RFPs, preparing pricing estimates, and delivering demonstrations and proofs of concept.

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Collaborate with sales and account management teams to scope engagements and communicate technical value to prospective clients.

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Mentor engineers, review technical architectures and code, and guide delivery teams throughout implementation.

Requirements

The ideal candidate combines deep data engineering expertise with strong architectural capabilities and client-facing experience. You should be comfortable leading complex cloud transformation initiatives, influencing technical stakeholders, and contributing to presales activities while remaining closely involved in solution design and implementation.

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Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

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At least 5 years of experience in data analytics and architecture, including large-scale cloud deployments.

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At least 4 years of experience in client-facing roles, preferably within a professional services or consulting environment.

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Proven experience designing and implementing modern data lakehouses, data warehouses, and data pipelines across AWS, Azure, or Google Cloud Platform (GCP).

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Expert-level knowledge of Databricks and Apache Spark, which are essential for this position.

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Strong understanding of data modeling, ETL/ELT pipelines, data integration specifications, security policies, access controls, and cloud infrastructure configuration.

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Experience architecting scalable solutions across hybrid and multi-cloud environments.

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Demonstrated ability to develop proofs of concept, deliver technical presales presentations, and contribute to engagement pricing.

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Experience participating in technical discovery, solution design, RFP responses, and client demonstrations.

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Strong communication and presentation skills, with the ability to influence both technical teams and executive stakeholders.

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Excellent problem-solving and analytical skills, with the ability to navigate complex technical challenges.

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Proven ability to mentor engineers, provide technical guidance, and collaborate effectively with cross-functional teams.

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Familiarity with Google Workspace, macOS, Slack, and Atlassian tools.

Benefits

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Annual base salary ranging from $155,000 to $215,000, depending on experience, skills, qualifications, role scope, and budget.

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For remote positions, an indicated salary range of $170,000–$190,000 USD.

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Remote working opportunities across the United States and Ontario, Canada.

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Option to work from offices in Arlington, VA; Chicago, IL; New York, NY; or Toronto, Canada.

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Opportunity to work on enterprise-scale data modernization and AI transformation projects.

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Exposure to cutting-edge technologies and cloud platforms, with a strong focus on Databricks.

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Collaborative environment focused on technical excellence, innovation, and measurable client outcomes.

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Opportunities to mentor engineering talent and influence architectural standards across diverse industries.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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