The Senior Manager Internal Audit - IT is a strategic transformation leader responsible for the organization’s technology risk landscape. This role goes beyond traditional oversight; you will act as a technologist within the audit function, leveraging AI and data science to automate control environments while ensuring the digital backbone of our global operations—including Manufacturing and M&A integrations—remains secure, compliant, and efficient.

Individual contributor with significant leadership and cross-functional influence

Responsibilities: 

Innovation, AI & Audit Transformation

• AI-Enabled Control Testing: Architect and implement AI/Machine Learning models to transition from manual sample-based testing to 100% population testing.
• Annual SOX Audit: Lead SOX IT control design and operating effectiveness including identification of gaps, operating deficiencies, remediation plan and partnership with process owners to optimize control environment 
• Audit Workflow Automation: Leverage Generative AI and Robotic Process Automation (RPA) to automate the documentation of walkthroughs, drafting of audit reports, and the mapping of controls to regulatory frameworks.
• Continuous Control Monitoring (CCM): Partner with IT to build real-time dashboards that monitor key risk indicators (KRIs), moving the department toward a "continuous audit" model.
• Predictive Risk Insights: Use data signals to identify emerging risks in the Quote-to-Cash and Manufacturing cycles before they manifest as material weaknesses.
• Lead the development of automated risk-sensing capabilities and Key Risk Indicators (KRIs) within the ERM framework, leveraging data analytics to provide real-time assurance over tech-stack dependencies and third-party vendor ecosystems

Business Process & Systems Excellence

• Automated Control Testing: Review the automated controls within core value streams such as Quote-to-Cash (Q2C) and Procure-to-Pay (P2P) to ensure data integrity and system reliability.
• Annual SOX Audit: Lead SOX control design and operating effectiveness including ITGC’s,  identification of gaps, operating deficiencies, remediation plan and partnership with process owners to optimize control environment
• SDLC & Implementation: Perform pre- and post-implementation reviews for major system upgrades or ERP deployments to prevent "go-live" control failures.

Business Combinations & M&A Integration

• IT Due Diligence: Lead IT-focused risk assessments for business combinations, evaluating the target company’s security posture and control maturity.
• Post-Merger Integration (PMI): Direct the integration of acquired entities into the corporate Internal Control Framework (COSO), managing the risks associated with data migration and system cutovers.

SOX & Regulatory Compliance (GovCon Focus)

• ITGC Ownership: Lead the testing of IT General Controls (ITGC) and IT Application Controls (ITAC) for SOX 404 compliance.
• Regulatory Standards: Ensure IT systems meet stringent government contracting standards, including NIST 800-171, CMMC, and FAR/DFARS requirements.

You’d be a good fit with: 

Experience & Education

• Education: Bachelor’s degree in Management Information Systems (MIS), Computer Science, or Accounting.
• Experience: 8–10+ years of progressive experience in IT Audit, IT Risk, or Cyber Consulting (Big 4 or large-scale complex corporate environments preferred).

Technical & Professional Skills

• Certifications: CISA required. CISSP, CRISC, or CISM highly preferred.
• Framework Mastery: Deep understanding of COBIT, NIST, ISO 27001, and the COSO Internal Control Framework.
• Influencing Without Authority: Exceptional "executive presence" with the ability to translate complex "tech-speak" into actionable business risks for senior leadership and IIA Standards.

You’d be a great fit with:

• M&A Track Record: Proven experience managing IT control transitions during business combinations or system consolidations.
• Industry Savvy: Strong background in manufacturing or organizations engaged in government contracting.“Nice-to-haves” / desired or preferred experience
• Modern Audit Toolkit: Hands-on experience with SQL, Python, or AI-based audit tools (e.g., Alteryx, MindBridge, or custom GPT agents). 
• Systems & Data: Proficiency in ERP systems (Netsuite/Oracle, Snowflake/DataBricks)

Location: College Park, MD
Travel: Up to 25% 
Job ID: 1383

The approximate base salary range for this position is $128,445 - $167,497. The total compensation package includes base, bonus, and equity.

CSQ426R15

PLEASE NOTE:
Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. The position is based in the Washington, D.C., Maryland, or Virginia metropolitan area and includes periodic on‑site work and client collaboration. Candidates with an active Secret or higher clearance are strongly encouraged to apply.

At Databricks, we are on a mission to empower our customers to solve the world's toughest data problems by utilizing the Databricks Data Intelligence Platform. As a Delivery Solutions Architect (DSA), you will play an important role during this journey. You will collaborate with our sales and field engineering teams to accelerate the adoption and growth of the Databricks Platform in your customers. You will also help ensure customer success by increasing focus and technical accountability to our most complex customers who need guidance to accelerate usage on Databricks workloads that they have already selected, helping them maximise the value they get from our platform and the return on investment.

This is a hybrid technical and commercial role. It is commercial in the sense that you will drive growth in your assigned customers and use cases through leading your customers' stakeholders, building executive relationships, orchestrating other focused/specialized teams within Databricks, and creating and driving plans and strategies for Databricks colleagues to build upon. This is in parallel to being technical, with expectations being that you become the post-sale technical lead across all Databricks products. This requires you to utilize your skills and technical credibility to engage and communicate effectively with all levels of an organization. You will report directly to a DSA Manager within the Field Engineering organization. 

The impact you will have:

• Engage with Solutions Architects to understand the full use case demand plan for prioritised customers
• Lead the post-technical win technical account strategy and execution plan for the majority of Databricks use cases within our most strategic accounts
• Be the accountable technical leader assigned to specific use cases and customer(s) across multiple selling teams and internal stakeholders, creating certainty from uncertainty and driving onboarding, enablement, success, go-live and healthy consumption of the workloads where the customer has made the decision to consume Databricks
• Be the first contact for any technical issues or questions related to the production/go-live status of agreed-upon use cases within an account, oftentimes services multiple use cases within the largest and most complex organizations
• Leverage both Shared Services, User Education, Onboarding/Technical Services, and Support resources, along with escalating to expert-level technical experts, to build the right tasks that are beyond your scope of activities or expertise
• Create, own, and execute a point-of-view as to how key use cases can be accelerated into production, coordinating with Professional Services (PS) resources on the delivery of PS Engagement proposals
• Navigate Databricks Product and Engineering teams for new product Innovations, private previews, and upgrade needs
• Develop an execution plan that covers all activities of all customer-facing technical roles and teams to cover the below work streams:
• Main use cases moving from ‘win’ to production
• Enablement/user growth plan
• Product adoption (strategy and activities to increase adoption of Databricks’ Lakehouse vision)
• Organic needs for current investment (e.g. cloud cost control, tuning & optimization)
• Executive and operational governance
• Provide internal and external updates - KPI reporting on the status of usage and customer health, covering investment status, important risks, product adoption and use case progression - to your Technical GM

What we look for:

• U.S. citizenship 
• 7+ years of experience where you have been accountable for technical project/program delivery within the domain of Data and AI and where you can contribute to technical debate and design choices with customers 
• Programming experience in Python, SQL or Scala 
• Experience in a customer-facing pre-sales, technical architecture, customer success, or consulting role 
• Understanding of solution architecture related to distributed data systems
• Understanding of how to attribute business value and outcomes to specific project deliverables
• Technical program, or project management, including account, stakeholder and resource management accountability
• Experience in resolving complex and important escalations with senior customer executives
• Experience conducting open-ended discovery workshops,  creating strategic roadmaps, conducting business analysis and managing delivery of complex programmes/projects
• Track record of overachievement against quota, Goals or similar objective targets
• Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience
• Can travel up to 30% when needed

CSQ327R189

Lead Technical Program Manager, Retail - Professional Services

At Databricks, our core principles are at the heart of everything we do; creating a culture of proactiveness and a customer-centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user-friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement. You will be an essential part of this mission, using your technical expertise to demonstrate how our Data Intelligence Platform can help customers solve their complex data challenges. You'll work with a collaborative, customer-focused team that values innovation and creativity, using your skills to create customized solutions to help our customers achieve their goals and guide their businesses forward. Join us in our quest to change how people work with data and make a better world!

As a Lead Technical Program Manager at Databricks, you will be a key driver in our Professional Services team's mission to accelerate and de-risk customer outcomes. Your role is central to achieving project goals and maintaining exceptional customer satisfaction, particularly within our Retail customer base. While you are not expected to have hands-on coding experience, your technical acumen and strategic influence will be critical for guiding complex engagements to success. You will work closely with cross-functional teams to deliver excellence at every stage.

The Impact You Will Have

• Be responsible for the successful delivery of our most complex customer engagements by providing technical leadership and guidance to the implementation team.
• Guide technical teams through key architectural decisions, helping them navigate trade-offs between established and innovative approaches.
• Proactively identify and mitigate technical risks and dependencies that could impact project timelines and goals.
• Individually deliver on commitments by producing high-quality deliverables, status reports, program plans, and customer responses that require minimal rework.
• Effectively manage all aspects of a program, including scope, schedule, budget, risk, and resources, with a focus on technical complexity.
• Act as the primary point of escalation for customers regarding technical delivery issues and, as needed, escalate to other parts of Databricks for rapid resolution.
• Build trust and credibility with technical teams and stakeholders by clearly articulating Databricks’ vision and solutions and facilitating productive, goal-oriented meetings.

What We Look For

• Technical Acumen & Decision Making: A proven ability to stay current on technology trends and make sound technical decisions without being a hands-on coder.
• Program & Project Management: Experience managing large, complex engagements and mitigating unexpected technical challenges. Familiarity with managing the trade-offs between scope, budget, and timeline.
• Communication & Leadership: Excellent communication, negotiation, and conflict resolution skills. A track record of influencing technical teams and effectively tailoring messages for different audiences, from engineers to executives.
• Experience with BI, data management, and big data technologies is preferred.
• Proven ability to multitask and manage multiple engagements while delivering a high level of customer satisfaction.

Position Overview 

We are seeking a Lead Data Engineer to serve as a senior individual contributor—equivalent to a Staff or Principal Data Engineer—with full ownership of analytics data architecture and engineering standards. This hands‑on technical leadership role is part of a high‑impact analytics team responsible for enabling data‑driven decision‑making across satellite network planning, capacity and demand forecasting, network operations, and performance analytics. 

The Lead Data Engineer will design, build, and operate scalable, production‑grade data pipelines and analytical infrastructure to ensure high‑quality; reliable data is consistently available across global planning and operational workflows. This role defines how operational, network, and business data is ingested, modeled, governed, and consumed—transforming complex, heterogeneous datasets into trusted, decision‑ready analytics assets. 

While this position does not include people management, it carries significant technical ownership and influence. The Lead Data Engineer drives architectural strategy, establishes engineering best practices, and mentors analytics professionals to elevate data engineering maturity across the organization. 

 Success in this role is measured by enabling fast, confident, and consistent data‑driven decision‑making—not platform uptime alone. The focus is on delivering durable analytics foundations that support insight, alignment, and execution at scale 

Key Responsibilities 

Data Architecture & Platform Ownership 

• Own the end‑to‑end analytics data architecture, including ingestion, modeling, governance, and consumption patterns. 

• Design, build, and maintain scalable, reliable data pipelines supporting forecasting, network planning, and operational analytics. 

• Establish and operate a lakehouse‑style architecture (raw → normalized → curated). 
• Integrate diverse, complex operational and telemetry data sources into unified analytical and semantic models. 

Analytics Enablement & Decision Systems 

• Translate ambiguous business needs into durable data products, including curated datasets, semantic layers, and standardized KPIs. 

• Define KPI frameworks with consistent definitions, calculations, and refresh logic across teams. 

• Enable self‑service analytics by delivering trusted, well‑documented, discoverable datasets for BI and advanced analytics. 

  Data Quality, Reliability & Governance 

• Implement automated validation, monitoring, and freshness checks across critical pipelines. 

• Identify and resolve systemic data issues proactively, ensuring uninterrupted operational insights. 

• Design schemas and pipelines with governance needs in mind, including lineage, auditability, and certification. 

  Technical Leadership & Standards 

• Serve as the technical authority for analytics engineering and own architectural decisions. 

• Establish and enforce engineering best practices, including testing, version control, documentation, and modular SQL/Python patterns. 

• Mentor analysts and engineers to raise the quality and reliability of data products. 

• Capture metadata and ownership for scalable governance and enterprise cataloging. 

  Qualifications 

Education 

• Bachelor’s degree in computer science, data engineering, information systems, or a related technical field required. 

• Master’s degree preferred but not required. 

  Experience 

• A minimum of 7–10 years of experience in data engineering, analytics engineering, or related fields. 

• Proven experience designing and operating production‑grade data systems at scale. 

  Preferred Qualifications 

• Experience in telecom, satellite networks, IoT, or other high‑volume telemetry data environments. 

• Familiarity with predictive analytics, forecasting workflows, or ML‑driven feature pipelines. 

• Hands‑on experience implementing data quality frameworks, metadata systems, or data lineage tooling. 

• Experience supporting enterprise analytics on a global scale. 

  Soft Skills 

• Strong interpersonal skills and ability to collaborate across cross‑functional teams. 

• Excellent written and verbal communication skills. 

• Strong problem‑solving, debugging, and prioritization abilities. 

• Ability to operate effectively in fast‑moving, ambiguous environments. 

• Meticulous attention to detail, ensuring accuracy across all documentation and data products. 

• Demonstrated ability to translate complex technical concepts for non‑technical stakeholders. 

  Technology Stack 

• SQL (advanced proficiency for analytics‑grade modeling and transformations) 

• Python (data processing, automation, pipeline development) 

• Cloud platforms such as AWS (preferred), Azure, or GCP 

• ETL/ELT tools such as Airflow, Prefect, or Azure Data Factory 

• Modern data ecosystems including Databricks, Snowflake, Redshift, or similar 

• BI and analytics tools such as Power BI, Tableau, or Looker 

• Version control (Git), CI/CD, and modern testing frameworks 

 Physical Requirements 

• Ability to work in a standard office environment and use a computer for extended periods. 
• Occasional virtual or in‑person collaboration across global teams. 

This job description may not be inclusive to the duties and responsibilities listed. Additional tasks may be assigned to the employee from time to time or the scope of the job may change as needed by business demands. 

Position Overview 

The Data Governance Manager ensures end‑to‑end governance of satellite network data by establishing and maintaining standards, lineage, controls, and data‑quality frameworks that support reliable analytics for BPMS, RAN planning, mobility modeling, and regulatory reporting. This role defines data policies, validates data integrity, manages catalogs and lineage, enforces compliance, and ensures datasets meet engineering and planning requirements for accurate forecasting and operational decision‑making. The position reports to the Director of Network Planning & Analytics. 

This role is responsible for ensuring the trustworthiness, consistency, and governance of all satellite‑network data used for planning, modeling, and regulatory submissions. The Data Governance Manager establishes governance standards, lineage practices, and quality controls that enable dependable analytics across BPMS, RAN planning, and mobility modeling. By enforcing data‑quality and compliance standards, the role underpins accurate forecasting, defensible regulatory reporting, and sound operational decisions at scale. 

Key Responsibilities 

Data Governance Framework & Policy Management 

• Establish data governance models, principles, and operating processes for satellite‑network datasets. 

• Define and enforce data policies, standards, classification rules, lifecycle guidelines, and governance controls. 

• Integrate governance requirements into planning workflows, data pipelines, and change management processes. 

Metadata, Lineage, Cataloging & Data Quality 

• Maintain data catalog, glossary, metadata repositories, and end‑to‑end lineage for critical planning and mobility datasets. 

• Ensure data discoverability, semantic consistency, and traceability across engineering and analytics systems. 

• Set data quality SLAs/SLOs, implement automated checks, and lead remediation for issues impacting planning accuracy or regulatory reporting. 

Compliance, Risk Management & Cross‑Functional Alignment 

• Ensure data compliance with regulatory reporting, internal governance, and audit requirements. 

• Maintain audit‑ready artifacts and evidence of lineage, access governance, and data controls. 

• Define stewardship roles, collaborate with planning, engineering, and analytics teams, and align data definitions with system‑level needs. 

Analytics Enablement, Change Control & Reporting 

• Certify trusted datasets for BPMS analytics, RAN planning, mobility modeling, and forecasting. 

• Govern schema changes, version control, and data lifecycle evolution across platforms. 

• Deliver dashboards and reporting on data quality, lineage completeness, control adherence, risks, and remediation status. 

Deliverables 

• Data governance charter and operating model; documented policies, standards, and control catalogs. 

• Enterprise data catalog with business glossary, certified data products, and end‑to‑end lineage maps. 

• Data quality framework with rules, SLAs/SLOs, scorecards, monitoring, and remediation workflows. 

• Stewardship model with ownership matrix (RACI), steward roster, and council meeting cadence notes. 

• Approved data models and definitions for BPMS, RAN planning, mobility modeling, and regulatory datasets. 

• Access governance artifacts (classification, RBAC/ABAC matrices), audit logs, and evidence packs. 

• Change management procedures covering schema/versioning, impact assessments, and rollback plans. 

• Quarterly governance dashboards (DQ trends, lineage completeness, incidents, SLA adherence). 

• Regulatory reporting data packs with traceable lineage, control evidence, and sign‑off records. 

• Deployment readiness “data certification” checklists for market activation and ongoing operations. 

Qualifications 

Education 

• Bachelor’s degree in Computer Science, Data/Information Systems, Engineering, or a related field. 

• Master’s degree (Data/Information Management, Analytics, or similar) is a plus. 

Experience 

• 5+ years in data governance, data management, or metadata/lineage/data quality leadership roles. 

• Experience governing analytics for telecom/satellite, networks, or other complex, regulated data environments. 

• Proven track record establishing policies/standards, implementing catalogs/lineage, and enforcing data quality controls. 

• Demonstrated cross‑functional leadership partnering with engineering, analytics, and regulatory stakeholders. 

Required Technical Expertise 

• Data governance frameworks and artifacts (policies, standards, stewardship, RACI, control catalogs). 

• Metadata/lineage management and data catalog administration (e.g., Microsoft Purview, Collibra, Alation, Apache Atlas, Unity Catalog). 

• Data quality frameworks and tooling (rule‑based and statistical checks; DQ SLAs, scorecards, monitoring, remediation). 

• Master & reference data management (MDM/RDM) and semantic modeling (conceptual/logical/physical). 

• Access governance (RBAC/ABAC), data classification, PII handling, encryption, and audit logging. 

• Cloud data platforms and pipelines (Azure/AWS; Databricks/Spark; Snowflake/Redshift; Synapse/Delta Lake). 

• Practical understanding of network/satellite data domains (telemetry, coverage/traffic KPIs, mobility events, spectrum/logs, cost/deployment data). 

Professional Skills 

• Structured, detail‑oriented problem solving with a strong documentation mindset. 

• Ability to translate regulatory and engineering requirements into clear data controls and standards. 

• Excellent stakeholder management and communication across technical and non‑technical audiences. 

• Change management leadership for data lifecycle governance and platform evolution. 

• Ability to prioritize in a fast‑paced environment and drive outcomes through influence. 

Technology Proficiency 

• SQL for profiling and validation; familiarity with Python/Spark for quality rules and data tests. 

• Experience with data catalogs, lineage tools, and DQ platforms; BI tools (Power BI/Tableau) for governance dashboards. 

• Working knowledge of CI/CD for data (versioning, release pipelines) and collaboration tools (Jira/Confluence). 

• Strong proficiency with Microsoft Office Suite (Excel, PowerPoint, Word); Windows/Linux environments. 

Physical Requirements 

• Ability to work in a standard office or lab environment and operate a computer for extended periods. 

• Occasional travel for cross‑functional workshops, audits, and market activation readiness reviews. 

This job description may not be inclusive to the duties and responsibilities listed. Additional tasks may be assigned to the employee from time to time or the scope of the job may change as needed by business demands. 

CSQ227R175

PLEASE NOTE:
Due to federal contract requirements and client site access obligations, U.S. government Top Secret clearance is required to access classified information. The position is based in the Washington, D.C., Maryland, or Virginia metropolitan area and includes periodic on‑site work and client collaboration. Candidates with an active Secret or higher clearance are strongly encouraged to apply.

As a Resident Solutions Architect (RSA) on our Professional Services team, you will work with customers on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• Handle a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues
• Collaborate with the Databricks Technical, Project Manager, Architect and Customer teams to ensure the technical components of the engagement are delivered to meet customer's needs
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues

What we look for:

• US Top Secret Clearance Required TS/SCI Preferred this position
• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines
• Documentation and white-boarding skills
• Experience working with clients and managing conflicts
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects
• Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience
• Ability to travel up to 30% when needed

FEQ227R208

Candidates in the listed region are encouraged for this role, we are open to remote candidates with a preference in the North East or Midwest at one of our office hubs.  

Mission

Reporting to a Director, Field Engineering, the Sr. Manager, Field Engineering will help lead a team of Solutions Architects (SAs) for the Financial Services segment of Databricks’ Regulated Industries Field Engineering team. You will lead and promote a diverse team focusing on enterprise software, big data/analytics, data engineering, data science, data warehousing and generative AI. Leading the technical sales team, you will partner with Sales (and other Field Engineering technical segments) to increase revenue and help customers achieve success through Databricks’ Data Intelligence Platform. You wil scale and maintain an outstanding Field Engineering team that is efficient in its operations to help accelerate Databricks' growth in the market.

The Impact You Will Have

• You will hire, train, and grow a team of Solutions Architects for a company in high-growth mode
• Make your customers extremely successful with Databricks and provide outsized value to their businesses
• You will maintain a robust hiring pipeline of highly qualified, bar-raising candidates
• You will establish relationships across the business to make your customers and team successful
• You will keep your team of SAs ahead of the technical curve by ensuring they maintain advanced knowledge of the Databricks technology stack
• You will ensure that your team is continuously learning and working to provide our customers with the most comprehensive solutions for their needs

What We Look For

• Proven experience building and leading technical pre-sales teams - hiring, on-boarding, coaching and mentoring those teams to mature and grow into highly capable individual operators as well as exceptional team-players
• 10+ years of experience in the data space with a technical product (i.e. data warehousing, big data, machine learning, or more recently with generative AI)
• Trusted advisor to technical executives that guide strategic data infrastructure decisions
• Lead a team through best practices for technical qualification, technical validations, architecture discussions, and product demonstrations
• Establish and foster external partnerships with systems integrators (SIs) and independent software vendors (ISVs) that maximize and accelerate client success
• Strong understanding of consumption-driven business models and the recipes for long term growth and success
• Experience hiring candidates that continually raise the bar, ramping them up to be successful, and promoting into larger roles
• Create a positive culture and morale for the team - fostering strong working relationships between Field Engineering, Sales, and other important internal cross-functional teams
• Experience working cross-functionally with other teams such as Sales, Product Management, Engineering, and Customer Success
• Must be technical enough to earn the trust of Engineering talent and leadership at Databricks
• Ability to influence and review complex architectures; guiding your team and customers towards ideal solutions - that scale

FEQ427R261

Mission

We are seeking a Sr. Manager, Solutions Architects (SAs) to lead our Intelligence Community (IC), Navy, Air Force and Space Force team. You will lead and promote a dynamic team focusing on enterprise software, big data/analytics, data engineering, data science, data warehousing and generative AI. Leading the technical sales team, you will partner with Sales (and other Field Engineering technical segments) to increase revenue and help customers become wildly successful. You'll scale and maintain an outstanding Field Engineering team that operates efficiently to help accelerate Databricks' market growth.

The Impact You Will Have

• Alongside the Sales Director, you will set the vision and strategy for how this team will accelerate transformative outcomes for our IC and DoW customers
• You will hire, train, lead and grow the Solutions Architect team for a company in high-growth mode.
• Help your customers achieve exceptional success with Databricks and deliver substantial value to their businesses.
• You will maintain a robust hiring pipeline at all times.
• Establish relationships across the business to make your customers and team successful.
• Keep your team of SAs ahead of the technical curve. An SA adds value by maintaining advanced knowledge of the technology stack. You will make sure that your team is continuously learning and working to provide our customers with the most comprehensive solutions for their needs

What We Look For

• Proven experience building and leading technical pre(or post)-sales teams - hiring, on-boarding, and enabling pre(or post)-sales professionals
• 5+ years of experience in the data space with a technical product (i.e. data warehousing, big data, machine learning, or more recently with generative AI).
• Alternatively, 5+ years of experience in mission-focused space impacting the IC or DoW from a technology perspective
• Trusted advisor to technical executives that guide strategic data infrastructure decisions.
• Lead a team through best practices for technical qualification, technical validations, architecture discussions, and product demonstrations.
• Strategic mindset focused on driving customer outcomes in an accelerated fashion
• Experience hiring candidates that continually raise the bar, ramping them up to be successful, and promoting into larger roles.
• Create a positive morale for the team and help foster a working relationship between Field Engineering, Sales, and other important internal cross-functional teams.
• Experience working cross-functionally with other teams such as Sales, Product Management, Engineering, and Customer Success.
• Technical and business skills to earn the trust of Engineering talent and leadership at Databricks.
• Demonstrated architectural influence. Able to influence and review complex architectures; guiding your team and customers towards ideal solutions - that scale.

FEQ127R326

Mission

Solutions Architects at Databricks lead the growth of the Databricks Unified Analytics Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science and machine learning. As a member of our team, you will exercise and develop expertise in those areas, using open-source projects such as Apache Spark, MLflow, and Delta Lake. This is a customer-facing role, where you will work with customers, your teammates, the product team, and our post-sales teams, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish value. In that process, you will build relationships with our customers, find and build champions, and become a trusted advisor. You will report to the Field Engineering Manager for the team.

The impact you will have:

• Partner with the sales team to help customers understand how Databricks can help solve their business problems
• Provide technical leadership for customers to evaluate and adopt Databricks
• Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
• Build and present references architectures, how-tos, and demo applications for customers
• Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars
• Travel to customers in your region

What we look for:

• 8+ years in a customer-facing pre-sales, technical architecture, or consulting role
• Experience designing and architecting distributed data systems
• Comfortable programming in, and debugging, at least one of: Python, Scala, Java, SQL, or R
• Experience supporting Public Sector clients
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Warehousing (Ex: SQL, OLTP/OLAP/DSS)
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• US Citizen

FEQ127R165

Mission

Solutions Architects at Databricks lead the growth of the Databricks Unified Analytics Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science and machine learning. As a member of our team, you will exercise and develop expertise in those areas, using open-source projects such as Apache Spark, MLflow, and Delta Lake. This is a customer-facing role, where you will work with customers, your teammates, the product team, and our post-sales teams, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish value. In that process, you will build relationships with our customers, find and build champions, and become a trusted advisor. You will report to the Field Engineering Manager for the team.

The impact you will have:

• Partner with the sales team to help customers understand how Databricks can help solve their business problems
• Provide technical leadership for customers to evaluate and adopt Databricks
• Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
• Build and present references architectures, how-tos, and demo applications for customers
• Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars
• Travel to customers in your region

What we look for:

• 5+ years in a customer-facing pre-sales, technical architecture, or consulting role
• Experience designing and architecting distributed data systems
• Comfortable programming in, and debugging, at least one of: Python, Scala, Java, SQL, or R
• Experience supporting Public Sector clients
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Warehousing (Ex: SQL, OLTP/OLAP/DSS)
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• US Citizen

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Mission

Solutions Architects at Databricks lead the growth of the Databricks Unified Analytics Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science and machine learning. As a member of our team, you will exercise and develop expertise in those areas, using open-source projects such as Apache Spark, MLflow, and Delta Lake. This is a customer-facing role, where you will work with customers, your teammates, the product team, and our post-sales teams, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish value. In that process, you will build relationships with our customers, find and build champions, and become a trusted advisor. You will report to the Field Engineering Manager for the team.

The impact you will have:

• Partner with the sales team to help customers understand how Databricks can help solve their business problems
• Provide technical leadership for customers to evaluate and adopt Databricks
• Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
• Build and present references architectures, how-tos, and demo applications for customers
• Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars
• Travel to customers in your region

What we look for:

• 8+ years in a customer-facing pre-sales, technical architecture, or consulting role
• Experience designing and architecting distributed data systems
• Comfortable programming in, and debugging, at least one of: Python, Scala, Java, SQL, or R
• Experience supporting Public Sector clients
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Warehousing (Ex: SQL, OLTP/OLAP/DSS)
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• US Citizen