Architect, Data Engineering

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Architect, Data Engineering based in United States. As a Data Engineering Architect, you will design and lead modern, scalable data platforms and pipelines for enterprise clients across a range of industries. You will shape technical strategies and architectures that turn complex data environments into reliable, high-performing business solutions. The role is deeply hands-on, covering lakehouse and warehouse implementations, cloud data platforms, ingestion, transformation, and real-time processing. You will work closely with client stakeholders, delivery teams, sales, and account partners to translate business objectives into effective technical solutions. You will also guide engineers through implementation, review architectures and code, and help teams navigate complex technical challenges. The position offers significant exposure to emerging data technologies, technical discovery, presales, and high-impact modernization initiatives. It is an ideal opportunity for an experienced architect who combines deep data engineering expertise with strong consulting and client-facing capabilities. 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.