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Vacatia

Senior Databricks Engineer (Hybrid flexibility available)

Vacatia, Portland, Oregon, United States, 97204

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Senior Databricks Engineer (Hybrid flexibility available)

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Senior Databricks Engineer (Hybrid flexibility available)

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Vacatia Senior Databricks Engineer (Hybrid flexibility available)

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Senior Databricks Engineer (Hybrid flexibility available)

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Vacatia Join Vacatia and Help Power the Future of Vacation Experiences Through Data and AI

At Vacatia, we’re transforming how families and travelers vacation and how great data supports that mission. As a leading hospitality and resort management company, we blend personalized guest service with smart, scalable technology. Now, we’re hiring a

Senior Databricks Engineer

in Portland, Oregon, to design and build data infrastructure, integrations, pipelines, models, and reporting layers that fuel data-driven decisions and AI-infused workflows across our growing portfolio of resorts.

Why You’ll Love Working at Vacatia

Emphasis on AI: Vacatia technology teams are transitioning to an AI-first mentality and toolset. This initiative has the full support from our executive team, and Databricks AI capabilities will be central to our efforts. Designing Databricks at Scale: You will lead our development of Databricks infrastructure, to compliment existing infrastructure in Fivetran, Snowflake, and dbt. You will design a Databricks implementation that can scale agentic AI capabilities throughout our business and technology. Impact Behind the Scenes: Enable powerful reporting and self-service analytics that drive decisions in operations, marketing, finance, and product. Focus on Performance & Quality: Join a team that values well-architected data solutions, clean models, pipeline reliability, and ultimately, enabling tangible business impact. Growth & Collaboration: Work closely with analytics engineers, analysts, and business stakeholders to elevate our analytics maturity, deliver impactful insights, and push the limits of what AI can do for us.

Your Impact

Lead Vacatia’s adoption of AI capabilities in Databricks and beyond, using AI agents with our codified semantic layer definitions and application gateways like MCP servers Optimize data integration workflows from cloud apps, APIs, and operational databases for reusability and performance Design, develop, and maintain scalable ELT pipelines in Databricks using PySpark, SQL, and Delta Lake to compliment our existing ELT pipelines in Snowflake Implement data quality checks, lineage tracking, and transformation logic to support trusted reporting and analysis Create and manage curated data models and semantic layers for BI use cases in platforms such as Tableau, Slack, and Salesforce Collaborate with business and product stakeholders to translate analytical needs into clean, well-structured datasets and reporting Maintain clear documentation and definitions of our semantic layer to enable transparency, reusability, and team knowledge sharing Monitor and tune performance of jobs, queries, and workloads for speed, cost efficiency, and scalability Support experimentation, A/B testing, and KPI definition across product, marketing, and operations teams

Requirements

What You Bring

Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, or a related field Minimum of 3 years of experience in data engineering or analytics engineering, ideally in a high-growth environment Deep experience with Databricks, PySpark, SQL, and Delta Lake in production settings Strong understanding of data modeling principles, including dimensional models, star, and snowflake schemas Familiarity with orchestration and transformation tools such as dbt Cloud (preferred), or Airflow Experience supporting reporting tools like Tableau (preferred), Power BI, or Looker Knowledge of best practices in data governance, observability, and CI/CD for data pipelines Bonus: Experience in hospitality, travel tech, or property operations analytics

Compensation $150,000 - $200,000 plus stock options and benefits

How You’ll Ramp

By the 30 day mark, you’ll be…

Up and running on our tools and platforms, roughly knowing the lay of the land Learning about the timeshare industry and how Vacatia’s business works Meeting your new colleagues and learning who does what Teaching the team about Databricks capabilities Setting up Databricks to support some of our initial use cases Triaging and resolving technical difficulties in Databricks

By the 60 day mark, you’ll be…

Building familiarity with how Vacatia’s data models and business processes work Collecting feedback and iterating on solutions delivered to initial use cases Contributing to strategic design decisions on how we should further develop Databricks Contributing to a Databricks development roadmap

By the 90 day mark, you’ll be…

Quantifying the impact of solutions delivered thus far Contributing to internal conversations on data organization and structure, broadly Chipping away at the Databricks development roadmap Digging in on more challenging agentic AI use cases, such as automating business processes Coordinating and mentoring others, as they begin contributing to Databricks development

Our Values

Start with what the customer wants and work backwards to a solution Earn the respect and trust of those dependent on you Hire and develop the best. If you don't, none of your hard work matters Debate rigorously but commit wholly. We're one company. Always follow-through Be deliberate Be frugal, constraints breed innovation Never be satisfied, there's always a better way Leaders serve Think big, remain curious and be self-aware Culture is a culmination of every action, every day

Be Part of Something Bigger

If you’re excited to build scalable data pipelines and models that power real-world hospitality operations and drive smarter decisions, and you’re passionate about clean, high-performance data solutions, we’d love to meet you.

Apply today and help Vacatia shape the future of vacations through powerful analytics and data engineering. Seniority level

Seniority level Mid-Senior level Employment type

Employment type Full-time Job function

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