Specialist Solutions Architect - Azure Cloud Platform & Infrastructure

Specialist Solutions Architect - AI/ML

Databricks

FEQ327R186 - MFG FEQ227R247 - CMEG As an AI/ML Specialist Solutions Architect (SSA), you will be the trusted technical ML & AI expert to both Databricks customers and the Field Engineering organization. You will work with Solution Architects to guide customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying cutting-edge technologies in GenAI, MLOps, and ML more broadly, expanding your impact through mentorship, and establishing yourself as an AI thought leader. This role can be remote.  The impact you will have: * Architect production-level ML & AI workloads for customers using our unified platform, including agents, end-to-end ML pipelines, training/inference optimization, integration with cloud-native services, MLOps, etc.   * Serve as a trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems (tool-calling agents, multi-agent orchestration, guardrails), natural language querying of structured data, AI evaluation and observability, and monitoring systems * Build, scale, and optimize customer AI workloads and apply best-in-class MLOps to productionize these workloads across a variety of domains * Provide advanced technical support to Solution Architects during the technical sale, ranging from feature engineering, training, tracking, serving, to model monitoring, all within a single platform, as well as participating in the larger ML SME community in Databricks * Collaborate cross-functionally with the product and engineering teams to represent the voice of the customer, define priorities, and influence the product roadmap, helping with the adoption of Databricks’ AI offerings What we look for: * 5+ years of hands-on industry ML experience in at least one of the following: * ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring. * AI Engineer: Experience with the latest techniques in LLMs & agentic systems, including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI * Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience * Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike * Passion for collaboration, life-long learning, and driving business value through ML & AI * [Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role * Can meet expectations for technical training and role-specific outcomes within 3 months of hire * Can travel up to 30% when needed   Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.   Local Pay Range $180,000—$247,500 USD About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Specialist Solutions Architect - Data Engineering & Warehousing

Databricks

FEQ327R455 - DNB FEQ327R257 - Emerging FEQ327R204 - FinS As a Specialist Solutions Architect (SSA) - Data Engineering and Warehousing, you will guide customers through cloud data engineering transformations across a wide variety of use cases. In this customer-facing role, you will collaborate with and support Solutions Architects. This requires hands-on production experience with large-scale data engineering technologies and lakehouse architecture. The SSA teams help customers navigate evaluations and successfully plan production for their business intelligence workloads while aligning their technical roadmap with the Databricks Data Intelligence Platform. As a deep go-to expert reporting to the Specialist Field Engineering Manager, you will continue to strengthen your technical skills through mentorship, continuous learning, and internal training programs. In this role, you will establish yourself as a leader in the data engineering and warehousing specialty. The impact you will have: * Provide technical leadership to guide strategic customers to successful implementations on big data projects and large-scale data warehousing workloads. * Prove the value of the Databricks Intelligence Platform for customer workloads by architecting production workloads, including end-to-end pipeline load performance testing and optimization. * Architect production-level data pipelines, including end-to-end pipeline load performance testing and optimization. * Become a technical expert in an area such as data lake technology, big data streaming, or big data ingestion and workflows. * Assist Solution Architects with more advanced aspects of the technical sale, including custom proof of concept content, estimating workload sizing, and custom architectures. * Provide tutorials and training to improve community adoption (including hackathons and conference presentations). * Contribute to the Databricks Community. What we look for: * 5+ years of experience in a technical role with deep expertise across the following areas: * Software / Data Engineering: Hands-on experience with data ingestion, streaming technologies (e.g., Spark Streaming, Kafka), performance tuning, troubleshooting, and debugging Spark or other big data solutions. * Data Applications Engineering: Experience building data-driven use cases, such as risk modeling, fraud detection, and customer lifetime value (LTV). * Data Warehousing: Advanced query tuning, troubleshooting, data governance, and debugging MPP data warehouses or big data solutions. Experience migrating workloads from EDW systems (e.g., traditional SQL, Redshift, Snowflake, Synapse, EMR) across OLAP & OLTP workloads. * Data Observability: Experience with SIEM tools (e.g., Splunk, Elastic, Sentinel), telemetry/high-velocity log ingestion, and anomaly detection. * Proven track record of maintaining, scaling, and extending production data systems to evolve with complex business needs. * Deep expertise across multiple core data engineering domains, including: * Designing and scaling cost-efficient, high-performance data workloads (ETL/ELT, analytics) in cloud environments. * Building and migrating large-scale data pipelines, including batch, CDC (Change Data Capture), and streaming ingestion. * Migrating on-premises or Hadoop-based data systems to modern cloud platforms (AWS, Azure, GCP). * Developing and managing modern lakehouse and warehouse systems, including Delta Lake technologies, data modeling, governance, and BI integration. * Production programming experience in SQL and at least one of the following: Python, Scala, or Java. * Strong familiarity with cloud infrastructure providers (AWS, Azure, or GCP) is highly desirable. * Degree or Equivalent: Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent professional experience. * [Preferred] Prior customer-facing experience in a pre-sales or post-sales technical role. * Ability to meet expectations for technical training and role-specific milestones within 6 months of hire. * Willingness to travel up to 30% as needed.   Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.   Local Pay Range $180,000—$247,500 USD About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Sr. Specialist Solutions Architect - Data Engineering & Warehousing

Databricks

FEQ327R204 As a Sr. Specialist Solutions Architect (SSA) - Data Engineering and Warehousing, you will guide customers through cloud data engineering transformations across a wide variety of use cases. In this customer-facing role, you will collaborate with and support Solutions Architects. This requires hands-on production experience with large-scale data engineering technologies and lakehouse architecture. The SSA teams help customers navigate evaluations and successfully plan production for their business intelligence workloads while aligning their technical roadmap with the Databricks Data Intelligence Platform. As a deep go-to expert reporting to the Specialist Field Engineering Manager, you will continue to strengthen your technical skills through mentorship, continuous learning, and internal training programs. In this role, you will establish yourself as a leader in the data engineering and warehousing specialty. The impact you will have: * Provide technical leadership to guide strategic customers to successful implementations on big data projects and large-scale data warehousing workloads. * Prove the value of the Databricks Intelligence Platform for customer workloads by architecting production workloads, including end-to-end pipeline load performance testing and optimization. * Architect production-level data pipelines, including end-to-end pipeline load performance testing and optimization. * Become a technical expert in an area such as data lake technology, big data streaming, or big data ingestion and workflows. * Assist Solution Architects with more advanced aspects of the technical sale, including custom proof of concept content, estimating workload sizing, and custom architectures. * Provide tutorials and training to improve community adoption (including hackathons and conference presentations). * Contribute to the Databricks Community. What we look for: * 8+ years of experience in a technical role with deep expertise across the following areas: * Software / Data Engineering: Hands-on experience with data ingestion, streaming technologies (e.g., Spark Streaming, Kafka), performance tuning, troubleshooting, and debugging Spark or other big data solutions. * Data Applications Engineering: Experience building data-driven use cases, such as risk modeling, fraud detection, and customer lifetime value (LTV). * Data Warehousing: Advanced query tuning, troubleshooting, data governance, and debugging MPP data warehouses or big data solutions. Experience migrating workloads from EDW systems (e.g., traditional SQL, Redshift, Snowflake, Synapse, EMR) across OLAP & OLTP workloads. * Data Observability: Experience with SIEM tools (e.g., Splunk, Elastic, Sentinel), telemetry/high-velocity log ingestion, and anomaly detection. * Proven track record of maintaining, scaling, and extending production data systems to evolve with complex business needs. * Deep expertise across multiple core data engineering domains, including: * Designing and scaling cost-efficient, high-performance data workloads (ETL/ELT, analytics) in cloud environments. * Building and migrating large-scale data pipelines, including batch, CDC (Change Data Capture), and streaming ingestion. * Migrating on-premises or Hadoop-based data systems to modern cloud platforms (AWS, Azure, GCP). * Developing and managing modern lakehouse and warehouse systems, including Delta Lake technologies, data modeling, governance, and BI integration. * Production programming experience in SQL and at least one of the following: Python, Scala, or Java. * Strong familiarity with cloud infrastructure providers (AWS, Azure, or GCP) is highly desirable. * Degree or Equivalent: Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent professional experience. * 3+ years of customer-facing experience in a pre-sales or post-sales technical role. * Ability to meet expectations for technical training and role-specific milestones within 6 months of hire. * Willingness to travel up to 30% as needed.   Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.   Local Pay Range $219,100—$301,300 USD About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.