Databricks Senior Solution Architect

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Requirements:

• 5+ years of experience in data engineering, data architecture, or related fields.
• Hands-on experience with Databricks is a must.
• Proficiency in cloud platforms (AWS, Azure, GCP), with strong knowledge of cloud-native technologies and services.
• Expertise in Python, Scala, and SQL for large-scale data processing.
• Experience in designing and implementing data pipelines, ETL processes, Dev/Ops, Security/Ops and data lakes.
• Familiarity with ML workflows and libraries such as TensorFlow, PyTorch, and scikit-learn.
• Strong experience with big data tools like Apache Spark, Hadoop, and Delta Lake.
• Excellent communication and interpersonal skills to effectively engage with both technical and non-technical stakeholders.

Responsibilities:

• Develop data architecture solutions and reference architectures for customers using Databricks.
• Work closely with clients to understand their business goals and technical needs, ensuring optimal use of the Databricks platform.
• Provide technical expertise during the pre-sales process, conducting workshops and proof-of-concept (POC) projects.
• Lead complex projects involving Databricks integration with cloud environments such as AWS, Azure, or GCP.
• Help customers optimize performance for large-scale data processing, streaming, and machine learning workflows on Databricks.
• Guide customers and internal teams on best practices in data engineering, machine learning, and AI using Databricks.
• Work cross-functionally with engineering, product, and sales teams to deliver successful implementations.
• Help the company identify market needs, define a Go To Market strategy, and execute on that strategy