Architect, Data Engineering

Team: IT

Location: US

Commitment: Full-time

Workplace Type: remote

Accountabilities:

• Develop forward-looking data strategies that align client business objectives with industry best practices.
• Design and oversee large-scale lakehouse and data warehouse implementations using Databricks and cloud-native technologies.
• Architect solutions that seamlessly integrate on-premises systems with multiple cloud environments.
• Design batch and streaming ingestion, real-time processing, and ELT/ETL architectures.
• Establish solutions that support security, privacy, compliance, and data quality at scale.
• Solve complex data engineering challenges and make strategic technical decisions that reduce delivery risks.
• Evaluate and introduce emerging technologies, methodologies, and engineering practices to continuously improve client solutions.
• Drive performance, cost optimization, scalability, reliability, and maintainability across data platforms.
• Mentor engineers, review architectures and code, and provide technical guidance throughout implementation.
• Lead technical discovery sessions and shape solution architectures based on client requirements.
• Support presales activities by responding to RFPs, developing technical proposals, delivering demonstrations, and building proofs of concept.
• Create technical blueprints and recommend appropriate tools, frameworks, and design patterns for client environments.
• Partner with sales and account teams to scope engagements and communicate technical solutions effectively.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
• 5+ years of experience in data engineering and architecture, including experience with large-scale cloud deployments.
• 4+ years of experience in client-facing roles, preferably within a professional services or consulting environment.
• Proven experience designing and implementing modern data lakehouses, warehouses, and data pipelines across AWS, Azure, or GCP.
• Expert-level knowledge of Databricks and Apache Spark.
• Experience developing proofs of concept, technical presales presentations, and engagement pricing.
• Strong understanding of modern data engineering architecture, cloud platforms, data integration, and processing patterns.
• Excellent client-facing communication skills, with the ability to influence both technical and executive stakeholders.
• Strong problem-solving and decision-making skills, particularly when working through complex or ambiguous technical challenges.
• Ability to mentor engineers and provide clear technical direction across delivery teams.
• Comfortable working across technical delivery, architecture, consulting, and presales responsibilities.
• Familiarity with Google Workspace, macOS, Slack, and Atlassian tools.
• Strong ability to translate business requirements into scalable, maintainable technical solutions.

Benefits:

• Base salary range of $155,000–$215,000 USD per year, depending on experience, skills, qualifications, role scope, and budget.
• Remote U.S. roles offer a salary range of $170,000–$190,000 USD.
• Remote work opportunities across the United States.
• Opportunity to work on large-scale data and AI modernization initiatives for enterprise clients.
• Exposure to Databricks, AWS, Azure, GCP, and modern cloud-native data technologies.
• Opportunity to work across diverse industries and complex technical environments.
• Significant ownership over data architecture, technical strategy, and solution delivery.
• Collaborative environment with opportunities to mentor engineers and influence technical practices.