Resident solution architect

Weekday AI · posted Sep 28, 2026

Open to candidates in India

Full-time · Senior

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What this job asks for

Extracted by RemoteHunt

Must have

  • •Databricks
  • •Apache Spark / PySpark
  • •SQL
  • •Data Engineering fundamentals
  • •Cloud platform experience (AWS, Azure, or GCP)
  • •Customer-facing / consulting experience

Nice to have

  • •Delta Lake
  • •Unity Catalog
  • •MLflow
  • •Kafka
  • •GenAI

Tools and technologies

Databricks, Apache Spark, PySpark, SQL, Delta Lake, Unity Catalog, AWS, Azure, GCP, Kafka, MLflow, Terraform, CI/CD, Snowflake, Hadoop

Read the full posting

This role is for one of Weekday’s clients Min Experience: 9+ years Location: India JobType: full-time

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

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