Senior Solutions Architect (AWS & DevOps)

• Senior Solution Architect - Databricks
• Job Summary
• We are looking for an experienced Senior Solution Architect with deep expertise in Databricks and modern data engineering technologies to lead the design, architecture, and implementation of scalable data platforms. The ideal candidate will work closely with customers to understand their business objectives, translate requirements into technical solutions, and deliver high-performance, cloud-based data platforms
• As a trusted technical advisor, you will provide architectural guidance, mentor engineering teams, and ensure best practices in data engineering, data governance, and platform optimization
• Experience
• 10+ years of overall experience in Information Technology
• 6+ years of hands-on experience designing and implementing solutions using Databricks
• Proven experience in architecting enterprise-scale data platforms and analytics solutions

Key Responsibilities

Collaborate with customers, business stakeholders, and technical teams to gather requirements and design scalable data platform architectures

Design and implement modern Data Lakehouse solutions using Databricks

Develop and optimize scalable data ingestion, transformation, and processing pipelines using Apache Spark

Define and implement data architecture following Medallion (Bronze, Silver, Gold) architecture principles

Lead solution design discussions, technical workshops, and architecture reviews with customers

Provide technical leadership and mentor development teams on Databricks best practices and modern data engineering techniques

Optimize Spark workloads for performance, scalability, and cost efficiency

Design secure, reliable, and highly available data solutions with appropriate governance and monitoring

Work closely with cross-functional teams including Data Engineers, Data Scientists, DevOps, and Cloud Architects to deliver end-to-end solutions

Identify opportunities for platform optimization, automation, and continuous improvement

Support pre-sales activities by providing technical consulting, solution presentations, architecture diagrams, and effort estimations when required

Required Technical Skills

Strong hands-on expertise in Databricks

Strong programming skills in Python and SQL

Extensive experience with Apache Spark (PySpark/Spark SQL)

Solid understanding of Data Lake and Lakehouse architectures

Experience implementing Medallion Architecture (Bronze, Silver, Gold layers)

Expertise in designing and maintaining scalable ETL/ELT pipelines

Strong knowledge of data modeling, partitioning, optimization, and performance tuning

Experience working with structured, semi-structured, and unstructured data

Good understanding of data quality, governance, and security best practices

Familiarity with CI/CD practices, version control (Git), and Agile methodologies

Preferred Skills

Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform

Knowledge of Delta Lake, Unity Catalog, Delta Live Tables, Databricks Workflows, and MLflow

Experience integrating Databricks with cloud-native data services and orchestration tools

Understanding of streaming technologies and real-time data processing

Experience with Infrastructure as Code (Terraform or similar) is a plus

Databricks or cloud certifications are highly desirable

Soft Skills

Excellent customer-facing and stakeholder management skills

Strong analytical and problem-solving abilities

Excellent verbal and written communication skills

Ability to lead technical discussions and influence architectural decisions

Strong collaboration and mentoring capabilities

Ability to manage multiple priorities in a fast-paced environment

What You'll Bring

A customer-first mindset with the ability to translate business requirements into scalable technical solutions

Strong architectural thinking with expertise in modern data platforms

Passion for building reliable, high-performance, and cost-effective data solutions

Ability to work independently while collaborating effectively across distributed teams