Resident Solution Architect

This role offers the opportunity to work directly with enterprise customers as a trusted technical advisor on complex data and AI initiatives. You’ll design scalable cloud data architectures and help organizations modernize their data platforms using Databricks and Lakehouse technologies. The position combines hands-on engineering with solution architecture, consulting, technical workshops, and customer enablement. You’ll work across Apache Spark, PySpark, SQL, Delta Lake, cloud platforms, data pipelines, and AI-related technologies. The role also provides ownership from early discovery and proof-of-concept stages through production deployment and adoption. It is well suited to an experienced data professional who enjoys solving complex technical challenges while communicating effectively with both engineering teams and business stakeholders.

• 9+ years of professional experience in data engineering, software engineering, solution architecture, or closely related technical disciplines.

• Strong hands-on expertise with Databricks, Apache Spark/PySpark, SQL, and modern data engineering practices.

• Proven experience designing and implementing data pipelines, data platforms, Lakehouse architectures, data warehouses, or large-scale data processing environments.

• Strong understanding of data engineering fundamentals, including ingestion, transformation, processing, storage, data quality, scalability, and reliability.

• Experience with at least one major cloud platform: AWS, Azure, or GCP.

• Demonstrated solution architecture and technical design experience, with the ability to translate complex customer requirements into scalable technical solutions.

• Strong customer-facing and consulting experience, ideally working directly with enterprise engineering, data, architecture, and leadership stakeholders.

• Excellent communication and presentation skills, with the ability to lead workshops, explain complex technical concepts, and influence technical decisions.

• Strong Python skills and practical experience applying programming to data engineering or analytics solutions.

• Experience with Delta Lake, Unity Catalog, MLflow, Kafka, streaming, data migration, MLOps, machine learning, GenAI, data governance, Terraform, CI/CD, Snowflake, or the Hadoop ecosystem is advantageous.

• Strong troubleshooting and problem-solving skills, particularly around data pipelines, performance, scalability, and production environments.

• Ability to work independently in a remote environment while managing multiple customer engagements and technical priorities.