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Job DescriptionJob Description
Job Title: Solution Architect
Location: Remote | Employment Type: Contract
About the Role
We are looking for a seasoned Solution Architect to design and implement scalable data and cloud architectures for modern enterprises. The ideal candidate will have extensive hands-on experience with Databricks , Delta Lake , and other enterprise-grade cloud solutions . You will work closely with cross-functional teams to define and execute technical roadmaps , deliver high-performance solutions, and drive innovation across analytics platforms and data-driven systems .
Key Responsibilities
Lead the design and implementation of cloud- data platforms , leveraging tools such as Databricks , Delta Lake , and MLflow .
Architect large-scale ETL/ELT pipelines , data lakes, and real-time/streaming data solutions for diverse business needs.
Collaborate with data engineers , data scientists , and stakeholders to translate business requirements into scalable technical solutions.
Integrate Databricks notebooks , Apache Spark , and cloud- services (e.g., AWS Glue , Azure Data Factory ) for both batch and real-time data processing .
Define and enforce data governance , security best practices , and tools like Unity Catalog , IAM , and encryption at rest/in transit .
Implement integration patterns using REST APIs , event-driven messaging (Kafka/Pub/Sub), and distributed systems design .
Participate in architectural reviews , performance tuning , and optimization across distributed compute frameworks.
Stay ahead of emerging technologies in data architecture , cloud infrastructure , and ML Ops practices.
Required Qualifications Bachelor’s or Master’s degree in Computer Science , Data Engineering , or a related field.
10+ years of experience in enterprise software or data architecture roles , specifically working with cloud- platforms.
Strong hands-on expertise with Databricks , Apache Spark , and Delta Lake for building scalable data solutions.
Proficiency in at least one cloud platform ( AWS , Azure , or GCP ), and working knowledge of key services like S3 , ADLS , BigQuery , or Redshift .
Familiarity with streaming platforms such as Kafka , Kinesis , or Azure Event Hubs .
Experience designing and deploying data lakehouses or analytics platforms .
Solid understanding of data modeling , data governance , and pipeline orchestration (e.g., Airflow , dbt ).
Skilled in performance optimization , data security best practices , and cloud cost management .
Excellent communication skills, with the ability to manage stakeholders and collaborate across teams.
Skills certifications in Databricks , AWS/Azure/GCP Solution Architecture , or TOGAF .
Knowledge of ML/AI workflows , model versioning , and ML Ops practices.
Familiarity with Unity Catalog , Great Expectations , or other data quality frameworks .
Previous experience working in regulated environments such as healthcare , finance , or insurance is a plus.
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Architect large-scale ETL/ELT pipelines , data lakes, and real-time/streaming data solutions for diverse business needs.
Collaborate with data engineers , data scientists , and stakeholders to translate business requirements into scalable technical solutions.
Integrate Databricks notebooks , Apache Spark , and cloud- services (e.g., AWS Glue , Azure Data Factory ) for both batch and real-time data processing .
Define and enforce data governance , security best practices , and tools like Unity Catalog , IAM , and encryption at rest/in transit .
Implement integration patterns using REST APIs , event-driven messaging (Kafka/Pub/Sub), and distributed systems design .
Participate in architectural reviews , performance tuning , and optimization across distributed compute frameworks.
Stay ahead of emerging technologies in data architecture , cloud infrastructure , and ML Ops practices.
Required Qualifications Bachelor’s or Master’s degree in Computer Science , Data Engineering , or a related field.
10+ years of experience in enterprise software or data architecture roles , specifically working with cloud- platforms.
Strong hands-on expertise with Databricks , Apache Spark , and Delta Lake for building scalable data solutions.
Proficiency in at least one cloud platform ( AWS , Azure , or GCP ), and working knowledge of key services like S3 , ADLS , BigQuery , or Redshift .
Familiarity with streaming platforms such as Kafka , Kinesis , or Azure Event Hubs .
Experience designing and deploying data lakehouses or analytics platforms .
Solid understanding of data modeling , data governance , and pipeline orchestration (e.g., Airflow , dbt ).
Skilled in performance optimization , data security best practices , and cloud cost management .
Excellent communication skills, with the ability to manage stakeholders and collaborate across teams.
Skills certifications in Databricks , AWS/Azure/GCP Solution Architecture , or TOGAF .
Knowledge of ML/AI workflows , model versioning , and ML Ops practices.
Familiarity with Unity Catalog , Great Expectations , or other data quality frameworks .
Previous experience working in regulated environments such as healthcare , finance , or insurance is a plus.
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