LovelyticsRemote
Architect, Data Engineering
United States of America
Full Time
5 hours ago
$170,000 - $190,000 USD
H1B Sponsor Likely
Key skills
Data engineeringData architectureCloud deploymentsDatabricksApache SparkData lakehouseData warehouseData pipelinesAWSAzureGoogle Cloud PlatformGoogle WorkspaceMacOSSlackAtlassianClient-facing communicationinfluence technical and executive stakeholdersAIArtificial IntelligenceETLELTData EngineeringAnalyticsSparkGCPCommunication
About this role
Lovelytics is a Databricks-focused data and AI consulting firm specializing in artificial intelligence, data, and analytics solutions. They are seeking a Data Engineering Architect to design and lead the build-out of modern, scalable data platforms and pipelines for clients across industries.
Responsibilities:
- Formulate forward-looking data strategies aligned with client business objectives and industry best practices
- Design and oversee large-scale lakehouse and warehouse implementations on Databricks (must-have) and other cloud-native technologies
- Create solutions that integrate on-premises and multiple cloud environments seamlessly
- Architect batch and streaming ingestion, real-time processing, and ELT/ETL patterns
- Ensure security, privacy, compliance, and data quality at scale on client engagements
- Tackle intricate data engineering challenges and make strategic decisions to de-risk delivery
- Introduce emerging technologies and methodologies to keep client solutions at the cutting edge
- Drive performance, cost optimization, scalability, and maintainability across data engineering solutions
- Mentor engineers, review architectures and code, and guide teams through implementation
- Lead technical discovery, shape solution architectures, respond to RFPs, and deliver demos and proofs of concept for data engineering engagements
- Create technical blueprints and recommend tools, frameworks, and design patterns aligned to client needs
Requirements:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 5+ years of experience in data engineering and architecture, including large-scale cloud deployments
- 4+ years in a client facing role, preferably in a professional services firm
- Proven track record designing and implementing modern data lakehouses, warehouses, and pipelines in AWS, Azure, or GCP
- Expert knowledge of Databricks and Spark (required)
- Experience creating proofs of concept, technical presales presentations, and pricing for engagements
- Strong client-facing communication skills with the ability to influence technical and executive stakeholders
- A tech stack of Google Workspace (email, tools), MacOS, Slack (internal comms), Atlassian