Resident Solution Architect (RSA) - Data & Databricks

Weekday 1; India; Remote; INR 4,000,000 - 7,000,000; Full time

Job summary

Weekday 1 is seeking a Resident Solution Architect (RSA) – Data & Databricks to lead cloud-based data analytics design for enterprise clients. You will drive architecture discussions, mentor data teams, and collaborate with sales and delivery to craft scalable solutions.

The role requires 8+ years in data engineering/architecture, deep Databricks experience, and proficiency in PySpark, Python, SQL across Azure, AWS, and GCP. Remote (India) with full-time engagement.

Qualifications

• 8+ years in Data Engineering, Architecture, or related field.
• Deep Databricks expertise with cloud data platforms.
• Strong Spark/PySpark, Python, and SQL skills.
• Experience designing scalable ETL/ELT pipelines and data warehouses.
• Proven ability to lead architecture workshops, POCs, and customer engagements.

Responsibilities

• Design end-to-end Data, Analytics, Lakehouse solutions using Databricks.
• Lead architecture discussions and technical demonstrations for enterprise clients.
• Develop scalable data pipelines across Azure, AWS, and GCP.
• Mentor Data Engineering teams and provide architectural direction.
• Collaborate with Sales, Delivery, Product, and Engineering on solutions.

Skills

Databricks

Data Engineering

Solution Architecture

PySpark

Python

SQL

Lakehouse Architecture

Delta Lake

Unity Catalog

Databricks SQL

Databricks Workflows

Azure

AWS

GCP

ETL/ELT pipelines

Data Warehousing

Performance tuning

Tools

Databricks Certification

Snowflake

Kafka

dbt

Terraform

CI/CD

MLflow

Job description

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟰𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟳𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟰𝟬-𝟳𝟬 𝗟𝗣𝗔)

Experience: 8+ yrs

Location: Remote (India)

Job Type: Full-time

We are looking for an experiencedResident Solution Architect (RSA) – Data & Databricksto lead the design and delivery of scalable, cloud-based data and analytics solutions for enterprise customers. The role requires strong expertise inDatabricks, Data Engineering, PySpark, Python, SQL, Lakehouse Architecture, and Cloud platforms.

The ideal candidate will combine deep technical expertise with strong customer-facing and consulting capabilities. You will work closely with enterprise stakeholders to understand complex business and technology requirements, design effective data solutions, lead architecture discussions and POCs, and provide technical direction to engineering teams.

Requirements

Key Responsibilities

• Design end-to-endData, Analytics, and Lakehouse solutionsusing Databricks.
• Develop and review scalable ETL/ELT pipelines and enterprise data platforms.
• Work hands-on withDatabricks, Apache Spark, PySpark, Python, and SQL.
• Design solutions usingDelta Lake, Unity Catalog, Databricks SQL, and Databricks Workflows.
• Develop scalable data architectures acrossAzure, AWS, and GCPenvironments.
• Conduct technical discovery sessions, architecture workshops, and solution discussions with enterprise customers.
• Understand business and technical requirements and translate them into scalable architecture and implementation approaches.
• PrepareHigh-Level Designs (HLD), Low-Level Designs (LLD), architecture diagrams, technical proposals, and solution documentation.
• Lead POCs, technical demonstrations, solution validations, and architecture assessments.
• Provide technical guidance, mentoring, and architectural direction to Data Engineering teams.
• Review data pipelines, architecture designs, code, and implementation approaches for scalability and maintainability.
• Troubleshoot and optimiseDatabricks and Spark workloadsfor performance, scalability, reliability, and cost efficiency.
• Support data platform modernisation, migration, and transformation initiatives.
• Collaborate with Sales, Pre-Sales, Delivery, Product, and Engineering teams on technical solutioning.
• Engage with senior customer stakeholders to communicate architecture decisions, technical recommendations, risks, and trade-offs.
• Identify opportunities to improve data platform architecture, engineering practices, automation, and operational efficiency.
• Stay current with developments across Databricks, cloud data platforms, distributed computing, and modern data engineering technologies.

What Makes You a Great Fit

• 8+ years of experiencein Data Engineering, Data Architecture, Solution Architecture, Big Data, or a closely related field.
• Strong hands-on expertise inDatabricksand enterprise data platforms.
• Strong knowledge ofApache Spark and PySpark.
• Advanced programming skills inPython and SQL.
• Strong understanding ofLakehouse Architecture, Delta Lake, Unity Catalog, Databricks SQL, and Databricks Workflows.
• Proven experience designing scalableETL/ELT pipelines, data platforms, data models, and data warehouses.
• Experience working with at least one major cloud platform:Azure, AWS, or GCP.
• Strong understanding of distributed data processing, scalability, reliability, and data platform architecture.
• Hands-on experience withperformance tuning and optimisationof Databricks and Spark workloads.
• Proven experience in technical solution design, architecture workshops, POCs, technical demonstrations, and solution validation.
• Strong customer-facing consulting experience with the ability to engageArchitects, CTOs, CDOs, Engineering Managers, and senior technology stakeholders.
• Excellent communication, presentation, stakeholder-management, and technical storytelling skills.
• Ability to provide technical leadership and mentorship to Data Engineering teams.
• Strong analytical and problem-solving skills with a structured approach to complex technical challenges.
• Experience withDatabricks certificationwould be an advantage.
• Exposure toSnowflake, Kafka, Spark Streaming, dbt, Terraform, CI/CD, MLflow, MLOps, GenAI, LLM/RAG, or data migrationis desirable.
• Strong ownership mindset with the ability to work independently in a remote, customer-facing environment.