Resident Solution Architect – Data, Databricks

Weekday (YC W21)

. Design end-to-end Data, Analytics, and Lakehouse solutions using Databricks .

Posted 10/8/2026full-timeRemote • IndiaSeniorLead💰 ₹4,000,000 - ₹7,000,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing scalable Data, Analytics, and Lakehouse solutions using Databricks, Apache Spark, and cloud platforms such as Azure, AWS, or GCP. Proven ability to lead technical discussions, provide mentorship, and optimize data architectures for performance and reliability.

Highest-signal resume keywords

Databricks ExpertiseApache Spark and PySparkETL/ELT Pipeline DesignCloud Data Platform ExperienceTechnical Solution Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData ArchitecturePython ProgrammingSQL ProgrammingLakehouse ArchitectureDelta LakeDatabricks SQLDatabricks WorkflowsPerformance TuningData Platform Modernization

Soft Skills

Excellent CommunicationStakeholder ManagementAnalytical Problem-SolvingTechnical StorytellingMentorship

Tools & Technologies

DatabricksAzureAWSGCPSnowflakeKafkaTerraformCI/CDMLflowMLOps

Certifications & Qualifications

Databricks Certification

Industry Keywords

Big DataData PlatformsDistributed ComputingData MigrationData Warehousing

Tech Stack

Tools & technologies

ApacheAWSAzureCloudETLGoogle Cloud PlatformKafkaPySparkPythonSparkSQLTerraformUnity

About the role

Key responsibilities & impact

Design end-to-end Data, Analytics, and Lakehouse solutions using Databricks
Develop and review scalable ETL/ELT pipelines and enterprise data platforms
Work hands-on with Databricks, Apache Spark, PySpark, Python, and SQL
Design solutions using Delta Lake, Unity Catalog, Databricks SQL, and Databricks Workflows
Develop scalable data architectures across Azure, AWS, and GCP environments
Conduct technical discovery sessions, architecture workshops, and solution discussions with enterprise customers
Translate business and technical requirements into scalable architecture and implementation approaches
Prepare High-Level Designs, Low-Level Designs, 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 optimise Databricks and Spark workloads for 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 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 Databricks, cloud data platforms, distributed computing, and modern data engineering technologies

Requirements

What you’ll need

8+ years of experience in Data Engineering, Data Architecture, Solution Architecture, Big Data, or a closely related field
Strong hands-on expertise in Databricks and enterprise data platforms
Strong knowledge of Apache Spark and PySpark
Advanced programming skills in Python and SQL
Strong understanding of Lakehouse Architecture, Delta Lake, Unity Catalog, Databricks SQL, and Databricks Workflows
Proven experience designing scalable ETL/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 with performance tuning and optimisation of 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 engage Architects, 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
Databricks certification would be an advantage
Exposure to Snowflake, Kafka, Spark Streaming, dbt, Terraform, CI/CD, MLflow, MLOps, GenAI, LLM/RAG, or data migration is desirable
Strong ownership mindset with the ability to work independently in a remote, customer-facing environment