Resident solution architect
LocationIndia
Typefull-time
SenioritySenior
Experience9+ yrs
DepartmentWeekday's Client via platform
Company size10,000+ people
PostedSep 28, 2026 · 2w ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
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, 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
Hadoop ecosystem
Skills
Databricks
Apache Spark
PySpark
SQL
Delta Lake
Unity Catalog
MLflow
Kafka
Terraform
CI/CD
Snowflake
Hadoop
AWS
Azure
GCP
Python
This role is for one of Weekday’s clients
Min Experience: 9+ years
Location: India
JobType: full-time
About the role
We are looking for an experienced Resident Solutions Architect with strong expertise in Databricks, Apache Spark, Data Engineering and Cloud Data Platforms.
The RSA will work closely with enterprise customers to understand complex data and AI requirements, design scalable architectures, lead technical engagements and help customers successfully implement and productionize solutions on the Databricks platform.
The ideal candidate combines strong hands-on technical expertise with excellent customer-facing, consulting and communication skills.
Requirements
Key Responsibilities
•
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 cloud platforms such as 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.
Required Skills
Must Have
•
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
•
GCP
•
Strong customer-facing / consulting experience
•
Architecture/design experience
•
Excellent communication and presentation skills
Good to Have
•
Delta Lake
•
Unity Catalog
•
MLflow
•
Kafka
•
Streaming
•
Data migration
•
MLOps
•
Machine Learning
•
GenAI
•
Data governance
•
Terraform / CI/CD
•
Snowflake
•
Hadoop ecosystem
Databricks’ own Solutions Architect requirements similarly emphasize customer-facing architecture, big-data/data-science expertise, SQL, programming, cloud and the ability to translate customer needs into technical solutions.
Must-have skills
Data Engineering, Python, Solution Architecture
Good-to-have skills
SQL, azure, Databricks