Resident Solution Architect

Weekday (YC W21)

. Work directly with enterprise customers as a trusted technical advisor .

Posted 9/29/2026full-timeRemote • IndiaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable data architectures using Databricks, Apache Spark, and SQL, while providing technical guidance and support for data engineering and cloud integration. Strong customer-facing skills and the ability to translate business requirements into technical solutions are essential.

Highest-signal resume keywords

DatabricksApache Spark / PySparkData EngineeringSolution ArchitectureCloud Integration (AWS, Azure, GCP)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLData Pipeline DesignLakehouse ArchitectureData MigrationMachine LearningDelta LakeUnity CatalogMLOpsPythonTerraform / CI/CD

Soft Skills

Excellent CommunicationCustomer-Facing ExperiencePresentation Skills

Tools & Technologies

DatabricksAWSAzureGCPKafkaSnowflakeHadoop Ecosystem

Industry Keywords

Data GovernanceBig Data ArchitectureStreamingTechnical WorkshopsArchitecture Demonstrations

Tech Stack

Tools & technologies

ApacheAWSAzureCloudGoogle Cloud PlatformHadoopKafkaPySparkPythonSparkSQLTerraformUnity

About the role

Key responsibilities & impact

Work directly with enterprise customers as a trusted technical advisor
Understand customer business and technical requirements and translate them into scalable data architectures
Design and implement modern Lakehouse / Data + AI architectures using Databricks
Develop and guide POCs, technical workshops, and architecture demonstrations
Work extensively with Apache Spark / PySpark, SQL, and Databricks
Design scalable data ingestion, transformation, and processing pipelines
Work with Delta Lake, Unity Catalog, and Databricks platform capabilities
Support data migration and modernization initiatives
Integrate Databricks with AWS, Azure, or GCP
Troubleshoot performance, scalability, reliability, and data pipeline issues
Work with customer engineering, data science, architecture, and leadership teams
Provide technical recommendations around data engineering, analytics, ML/AI, and cloud architecture
Create reference architectures, technical documentation, and implementation guidance
Support production deployment and adoption of Databricks solutions
Conduct technical workshops, enablement sessions, and knowledge-sharing activities

Requirements

What you’ll need

Minimum 9+ years of experience
Strong experience with Databricks
Strong Apache Spark / PySpark
Strong SQL
Strong Data Engineering fundamentals
Experience designing data pipelines / data platforms
Experience with Lakehouse / Data Warehouse / Big Data architecture
Experience with at least one cloud: AWS, Azure, or GCP
Strong customer-facing / consulting experience
Architecture/design experience
Excellent communication and presentation skills
Delta Lake, Unity Catalog, MLflow, Kafka, Streaming, Data migration, MLOps, Machine Learning, GenAI, Data governance, Terraform / CI/CD, Snowflake, and Hadoop ecosystem are good-to-have skills
Must-have skills: Data Engineering, Python, Solution Architecture
Good-to-have skills: SQL, Azure, Databricks