Architect, Data Engineering
New
J
JobgetherData engineering
Remote U.S. rolesFull-TimeSenior
Salary170,000 - 190,000 USD per year
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Job Details
- Experience
- 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.
- Required Skills
- AWSGCPAzureData engineeringSparkGoogle WorkspaceDatabricks
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 large-scale cloud deployments.
- 4+ years of experience in client-facing roles, preferably in professional services or consulting.
- Experience designing and implementing data lakehouses, warehouses, and 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 data engineering architecture, cloud platforms, data integration, and processing patterns.
- Ability to influence technical and executive stakeholders through client-facing communication.
- Ability to mentor engineers and provide technical direction across delivery teams.
- Familiarity with Google Workspace, macOS, Slack, and Atlassian tools.
Responsibilities
- Develop data strategies aligned with client business objectives and industry best practices.
- Design and oversee large-scale lakehouse and data warehouse implementations using Databricks and cloud-native technologies.
- Architect solutions integrating on-premises systems with multiple cloud environments.
- Design batch and streaming ingestion, real-time processing, and ELT/ETL architectures.
- Establish solutions supporting security, privacy, compliance, and data quality at scale.
- Evaluate emerging technologies, methodologies, and engineering practices for client solutions.
- Drive performance, cost optimization, scalability, reliability, and maintainability across data platforms.
- Mentor engineers, review architectures and code, and provide technical guidance during implementation.
- Lead technical discovery and shape solution architectures based on client requirements.
- Support presales by responding to RFPs, developing technical proposals, delivering demonstrations, and building proofs of concept.
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