Most Loved Workplace® Certified JobSr. Learning Platform Specialist
Most Loved Workplace® Certified JobAbout the Role
At Databricks, a Most Loved Workplace® certified employer in the Technology space, Democratizing data and AI for every organization worldwide.
<p data-pm-slice="1 1 []">CSQ227R13</p>
<h2><strong>About Databricks</strong></h2>
<p>Databricks is The data and AI company. More than 10,000 organizations worldwide rely on the Databricks Data Intelligence Platform to unify data, analytics, and AI. Founded by the original creators of Lakehouse, Apache Spark™, Delta Lake, and MLflow, Databricks is building the foundation for organizations to put data and AI to work.</p>
<h3><strong>The impact you’ll have</strong></h3>
<p>As a Senior member of the Learning Platforms team, you will shape the technical direction of the systems that help employees, partners, and customers build the skills they need to succeed with data and AI. You will operate as a broad platform owner - moving fluidly from product strategy and architecture to the hands-on engineering, cross-functional alignment, and reliable operations.</p>
<p>You will lead the design and delivery of intelligent, data-driven learning experiences that connect content, skills, assessments, and business outcomes. This is a high-impact individual contributor role for an individual who can turn ambiguous business problems into secure, scalable products!&nbsp;</p>
<h3><strong>What you’ll do</strong></h3>
<ul>
<li>Own the architecture and technical strategy for a portfolio of learning platforms and enablement products, from early discovery through production operation and evolution.</li>
<li>Lead the design and implementation of AI-powered capabilities, including recommendation systems, skill inference, intelligent search, personalization, and analytics-driven learning workflows.</li>
<li>Build secure, privacy-aware data systems that integrate information across learning, workforce, customer, and operational platforms.</li>
<li>Develop Databricks-native applications, data pipelines, APIs, automations, and user experiences that make complex learning processes simple and scalable.</li>
<li>Establish strong engineering practices for reliability, observability, testing, release management, access control, and lifecycle ownership.</li>
<li>Make pragmatic decisions and define integration strategies across learning management systems, lab environments, content platforms, identity systems, and internal data products.</li>
<li>Partner with business leaders to define product direction, prioritize roadmaps, clarify trade-offs, and deliver measurable outcomes.</li>
<li>Navigate complex requirements involving security, privacy, compliance, governance, and responsible use of AI.</li>
<li>Lead cross-functional technical programs involving multiple engineering teams and senior stakeholders, creating clarity and momentum in ambiguous environments.</li>
<li>Mentor engineers, raise the technical bar, contribute to hiring, and create reusable patterns that help the broader organization move faster.</li>
<li>Serve as a technical thought leader internally and externally through architecture documents, technical presentations, reusable guidance, and community engagement.</li>
</ul>
<h3><strong>What we’re looking for</strong></h3>
<ul>
<li>5-7 years of experience designing, building, and operating production software or data platforms, with a track record of leading work across organizational boundaries.</li>
<li>Demonstrated experience owning architecture and technical direction for complex, multi-system products.</li>
<li>Strong full-stack or platform engineering background, with depth in backend services, APIs, data pipelines, cloud infrastructure, and modern web applications.</li>
<li>Experience designing and operating AI- or data-intensive systems, such as recommendation engines, inference pipelines, search, personalization, or analytics products.</li>
<li>Fluency in Python or a similar production programming language, plus strong SQL and experience with relational and analytical data systems.</li>
<li>Experience with cloud platforms, distributed systems, identity and access management, security controls, and production operations.</li>
<li>Strong judgment around data privacy, governance, least-privilege access, and responsible AI.</li>
<li>Ability to communicate clearly with engineers, product managers, security and legal partners, and senior business leaders.</li>
<li>A track record of delivering results with minimal oversight while bringing structure to ambiguous problems.</li>
<li>A collaborative leadership style that combines technical depth, product thinking, pragmatism, and a bias for action.</li>
</ul>
<h3><strong>Preferred qualifications</strong></h3>
<ul>
<li>Experience with Databricks products and technologies such as Databricks Apps, Lakehouse data architectures, Unity Catalog, Delta Lake, Lakebase, Workflows, SQL Warehouses, or the Databricks SDK.</li>
<li>Experience integrating learning, content, assessment, identity, HR, or customer-facing platforms.</li>
<li>Experience building systems that serve both internal users and external customers or partners.</li>
<li>Experience scaling automation and operational workflows across large user populations or high-volume data sources.</li>
<li>Experience with modern frontend frameworks such as React and application frameworks such as Flask or FastAPI.</li>
<li>Experience mentoring senior engineers or leading technical programs across several teams.</li>
<li>Evidence of technical thought leadership through conference talks, publications, open-source work, or industry communities.</li>
</ul>
<h3><strong>About the team</strong></h3>
<p>The Learning Platforms team builds the digital ecosystem behind Databricks learning and enablement. We combine software engineering, data, AI, and product thinking to improve how people discover content, develop skills, practice with the platform, and measure progress. Our work spans learner experience, intelligent recommendations, platform integrations, operational automation, cost efficiency, and reliable delivery at scale.</p><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p>&nbsp;</p>
<p><strong>Pay Range Transparency</strong></p>
<p><span style="font-weight: 400; font-size: 14px;">Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.&nbsp; 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 anticipated 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 <a href="https://www.Databricks.com/sites/default/files/2024-08/us-pay-zone-mapping.pdf">here</a>.<br></span></p>
<p>&nbsp;</p></div><div class="title">Zone 1 Pay Range</div><div class="pay-range"><span>$139,000</span><span class="divider">&mdash;</span><span>$191,050 USD</span></div></div><div class="pay-input"><div class="title">Zone 2 Pay Range</div><div class="pay-range"><span>$125,000</span><span class="divider">&mdash;</span><span>$171,950 USD</span></div></div><div class="pay-input"><div class="title">Zone 3 Pay Range</div><div class="pay-range"><span>$118,100</span><span class="divider">&mdash;</span><span>$162,350 USD</span></div></div><div class="pay-input"><div class="title">Zone 4 Pay Range</div><div class="pay-range"><span>$111,200</span><span class="divider">&mdash;</span><span>$152,900 USD</span></div></div></div><div class="content-conclusion"><p><strong>About Databricks</strong></p>
<p><span style="font-family: arial, sans-serif;">Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&amp;T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on <a href="https://www.linkedin.com/company/Databricks">LinkedIn</a>, <a href="https://x.com/Databricks">X</a>, <a href="https://www.youtube.com/@Databricks">YouTube</a>, and <a href="https://www.instagram.com/databricksinc/?hl=en">Instagram</a>.<br><br><strong>Benefits<br><br></strong></span>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 <a href="https://docs.google.com/document/d/154un3e8Xav4BceOSlcYFZRGEuQI54xMxVydRwQn54eQ/edit?usp=sharing">here</a>.<br><br></p>
<p><strong>Our Commitment to Diversity and Inclusion</strong></p>
<p>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.</p>
<p><strong>Compliance</strong></p>
<p><strong><span style="font-weight: 400;">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.</span></strong></p>
<p><a href="https://www.Databricks.com/legal/applicant-privacy-notice" target="_blank"><strong><span style="font-weight: 400;">Applicant Privacy Notice</span></strong></a></p></div>
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Why This Is a Most Loved Workplace® Certified Job
Systemic Collaboration
As Databricks continues our rapid growth, we strive to maintain a culture as open and transparent as it was in Databricks’s early days. Making sure employees have regular access to our CEO and co-founders to hear directly about our vision and priorities helps our employees forge a connection between Databricks priorities and their daily work.
Positive Vision for the Future
Databricks’ culture principles are derived from an internal study of the behaviors that have led to high impact work at Databricks. These values have a direct impact on company culture and play a large part in connecting teams across the organization. We believe in being customer-obsessed, truth-seeking, operating from first principles, having a bias for action, and putting Databricks first. Our co-founders are fully involved in day-to-day operations, including business and technical reviews, working alongside our team members to ensure that we are always aligned with our values.
Alignment of Values
Databricks’ CEO and Co-founder, Ali Ghodsi leads by example with a focus on truth-seeking and first principles thinking, two of Databricks’ core values that stay true to Databricks’s origins in academia. He champions the importance of data and reason to question biases and inform decisions. Ali remains hands-on with research and development and hosts company-wide weekly all hands, with a CEO “ask me anytime” session at the beginning of every agenda. His transparency and accessibility are core to the open and collaborative culture of Databricks.
Respect
At Databricks, we cultivate an environment where all employees can bring their unique selves and are empowered to do the best work of their careers. To ensure all voices are heard and ideas are valued, we conduct annual culture and pulse surveys and host all-hands Q&As to collect feedback from all employees. We then report back to Databricks on the specific changes implemented from the feedback collected to ensure employees feel heard and that their feedback is valued. In addition, we invest in our seven Employee Resource Groups (ERGs) that offer support and employee engagement events for individuals from underrepresented backgrounds and allies.
Killer Outcomes
Databricks prioritizes offering an exceptional employee experience by investing in tools, workspaces, and community-building. Our collaboration-first, hybrid model offers flexibility with in-person touchpoints like our annual employee kickoff, weekly CEO all-hands with happy hours, and monthly team building budgets. We are especially focused on maintaining a culture of transparency, honesty, and trust, with leaders actively engaging across channels like Slack and all hands while also championing inclusion efforts through ERG sponsorship. These initiatives help our team feel connected, valued, and empowered to do their best work.
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