{"id":2543137,"url":"https://alion.io/job/databricks-solutions-engineer","title":"Solutions Engineer","company":{"id":15,"name":"Databricks","domain":"databricks.com","url":"https://alion.io/company/databricks","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":79,"open_postings":855,"ghost_share":0.27,"stale_share":0,"repost_share":0.001,"time_to_fill_p50_days":75,"computed_at":"2026-10-14T06:34:16Z"}},"role":"Solutions","role_family":"Solutions","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":108000,"max_usd":245000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":309},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"Databricks","optional":false},{"name":"Hadoop","optional":false},{"name":"Java","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-14T15:26:03Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T02:38:39Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"FEQ427R443\nSolutions Engineer\nAt Databricks, our core values drive everything we do; a culture of proactiveness and a customer-first mindset fuels our mission to create a unified platform that makes AI and data analytics accessible to everyone in their own context. This role is part of our programmatic effort to develop promising field engineers-offering a launchpad for the next generation of data leaders. We aim to build leaders who will drive both data and business strategy for our customers, leading the front lines of Databricks growth as well.\nWith our Data Intelligence Platform, we make it easy to turn insights into action while encouraging creativity, experimentation, and continuous improvement. You’ll play a key role in this mission, building upon your emerging technical skills in the area of solutions engineering, learn how to apply them in the Databricks platform and show customers how to tackle real-world data challenges. Solutions engineers go further than telling them what's possible, they build working prototypes and advise customer teams on how to get to production. You’ll join a collaborative, customer-obsessed team that thrives on innovation to help customers reach their goals. Come help us change how the world works with data-and shape your future while you're at it!\nThis will be an in-office role and candidatesmust be based in our New York City (Midtown location). Relocation assistance will not be provided.\nRecent graduate?: We’d love for you to explore our current internship openings on our careers page and submit your application for our roles designed for new college graduates.\nMore About Databricks\nYouTube\nThe impact you will have:\nForm successful relationships with customers throughout your assigned territory, providing technical and business value to Databricks customers in collaboration with Account Executives.\nOperate as an expert in AI and data analytics to excite customers about Databricks. You will develop into a ‘champion’ and trusted advisor on multiple areas of architecture, design, and implementation to lead to the successful adoption of the Databricks data and AI platform.\nAdopt a builder-first approach: move quickly from customer problem to working prototype by writing code, building demos, and creating reusable assets that accelerate customer outcomes. \nUse AI tools to increase your productivity and drive innovation.\nScale best practices in your field and support customers by authoring reference architectures, how-tos, demo applications, and help build the Databricks community in your region by leading workshops, seminars, and meet-ups.\nGrow your knowledge and expertise to the level of a technical and/or industry specialist.\nWhat we look for:\nThe ideal candidate has 2+ years of technical experience in a customer-facing solutions engineering role.\nBachelor's degree in Computer Science, Data Science, Information Systems, Engineering, or equivalent experience through work experience\nDemonstrates a builder mindset: preference for hands-on prototyping and learning-by-doing, with comfort using AI-assisted development tools to move faster\nHands-on experience with Python, Java, or Scala, and proficiency in SQL\nExperience with Big Data technologies (Ex: Spark, Hadoop, Kafka) and architectures is a plus\nAptitude to interact with customers confidently and professionally\nCan meet expectations for technical training and role-specific outcomes within 6 months of hire\nAbout Databricks\nDatabricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&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 LinkedIn, X, YouTube, and Instagram.\nBenefits\n 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.\nOur Commitment to Diversity and Inclusion\nAt 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. 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