Senior Resident Solution Architect

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.