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Analytics Engineer

At Kalibri Labs, we are helping to redefine and rebuild the way performance metrics are viewed in the hotel industry. We are looking for passionate, energetic, and hardworking people with an entrepreneurial spirit, who dream big and challenge the status quo. We are working on cutting-edge solutions for the industry as they navigate the recovery process. We are using our big data coupled with machine learning and AI to help highlight the path forward. Kalibri Labs is growing, so if you’re ready to make a difference and utilize your talents across a groundbreaking organization, please keep reading!

We are growing fast and building a team of curious, driven, and forward-thinking problem-solvers. We dream big, challenge the status quo, and live in the intersection of data, technology, and service. We are seeking those that have similar ambitions. If this excites you, you’ll thrive here! 

We are looking for an Analytics Engineer to build and scale our data infrastructure in a modern ELT technology stack. You’ll work in a cross-functional, agile team to construct data models that empower customers and stakeholders across product, customer success, and executive leadership.

Responsibilities

  • Build and maintain dbt data models that transform raw data into reliable, actionable products for the business

  • Implement and maintain a medallion-style architecture (bronze/silver/gold layers) data flows 

  • Write and maintain data tests and documentation to ensure and enforce data trustworthiness

  • Collaborate with analysts and stakeholders to define business logic and KPIs

  • Build, monitor, and improve data workflows with dbt Cloud, prefect, and snowflake

  • Develop python-based transformations, scripts, and automation that scales team velocity against a product roadmap

  • Develop analytics engineering standards to include testing, git-based VCS, CI/CD, data contracts, SLAs / SLOs, and code standards

  • Actively communicate daily progress on a cross-functional team, identify & overcome impediments, and help teammates resolve emergent issues

Skills & Requirements

  • 2–4 years of experience in a data analytics, analytics engineering, or data modeling role

  • Superb analytical skills. Able to break down challenges into component parts and reconstruct to derive insights

  • Demonstrated real-world proficiency writing complex, performant SQL transformations

  • Hands-on experience building and maintaining dbt Core/Cloud models in a production environment to include model development, orchestration, documentation, and testing

  • Confident working in modern cloud data platforms, ideally Snowflake

  • Comfortable scripting integrations and automations with Python

  • Experienced working with git in a CI/CD-based test and release environment

  • Experience building or contributing to a semantic layer using dbt, BI tools, or metric layers

  • Excellent written and verbal communication skills, including documenting logic and assumptions

Nice To Haves

  • Bachelor’s Degree in a technical or quantitative field

  • Experienced in a modern orchestrator such as Airflow, Dagster, or Prefect

The Benefits

  • All positions are fully remote.

  • We cover 75% of the cost of medical insurance premiums for employees & their dependents with three medical plans through Blue Cross, Blue Shield.

  • We cover 75% of the cost of dental and vision insurance premiums for employees & their dependents.

  • We provide a 50% 401k match of the first 6% of the employee's contribution (for a max of 3%).

  • We also provide $50,000 of life insurance, Long-term disability and an Employee Assistance Program.

  • All new hires receive a $250 allowance to help them set up their home office.

Average salary estimate

$80000 / YEARLY (est.)
min
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$70000K
$90000K

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What You Should Know About Analytics Engineer, Kalibri Labs

At Kalibri Labs, we're on a mission to transform the hotel industry's approach to performance metrics, and we need a passionate Analytics Engineer like you to help us achieve this. Based in Potomac, you'll join a dynamic team that's known for dreaming big and challenging the status quo. Our innovative solutions leverage big data, machine learning, and AI to guide the industry through recovery and beyond. As an Analytics Engineer, you'll play a crucial role in building and scaling our data infrastructure using a modern ELT technology stack. You’ll collaborate with cross-functional teams to create robust data models that drive impactful insights for our customers and stakeholders across product, customer success, and executive leadership. Your hands-on experience with tools like dbt, Snowflake, and Python will be essential as you maintain the reliability and trustworthiness of our data. Our team prides itself on its curiosity and problem-solving abilities, so if you're enthusiastic about leveraging your skills in a groundbreaking organization, then Kalibri Labs is the perfect place for you! Join us as we redefine data in hospitality today.

Frequently Asked Questions (FAQs) for Analytics Engineer Role at Kalibri Labs
What are the key responsibilities of an Analytics Engineer at Kalibri Labs?

As an Analytics Engineer at Kalibri Labs, you'll be responsible for building and maintaining dbt data models that transform raw data into actionable insights. You'll implement a medallion-style architecture, ensuring a smooth flow of data across multiple layers. Your work will involve collaborating with analysts to define key performance indicators (KPIs) and conducting thorough data tests and documentation to maintain data integrity and trustworthiness.

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What qualifications do I need to apply for the Analytics Engineer position at Kalibri Labs?

To qualify for the Analytics Engineer position at Kalibri Labs, you should have 2-4 years of experience in a data analytics, analytics engineering, or data modeling role. Proficiency in writing complex SQL transformations and hands-on experience with dbt Core/Cloud models in a production environment are essential. Familiarity with modern cloud data platforms like Snowflake and experience with Python scripting are also important for this position.

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How does Kalibri Labs support remote work for the Analytics Engineer role?

Kalibri Labs offers a fully remote working environment for the Analytics Engineer role, allowing you to work from the comfort of your home. This flexible setup ensures that you can maintain a healthy work-life balance while still being an integral part of a collaborative team that communicates effectively across different locations.

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What technical skills are required for success as an Analytics Engineer at Kalibri Labs?

Successful Analytics Engineers at Kalibri Labs should possess superb analytical skills, capable of dissecting challenges and reconstructing them to derive insights. Proficiency in SQL, dbt model development, and familiarity with cloud data platforms like Snowflake are crucial. Additionally, experience with Python scripting for automation and utilizing git in a CI/CD environment will set you up for success in this role.

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What benefits can I expect when working as an Analytics Engineer at Kalibri Labs?

At Kalibri Labs, you can expect a comprehensive benefits package that includes covering 75% of medical, dental, and vision insurance premiums for you and your dependents. Enjoy a 50% 401k match on contributions, life insurance, long-term disability coverage, and an Employee Assistance Program. Additionally, new hires receive a $250 allowance to set up their home office, emphasizing our commitment to employee well-being.

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Common Interview Questions for Analytics Engineer
What experience do you have with dbt for data modeling?

In preparing for this question, highlight your hands-on experience with dbt, outlining specific projects where you've utilized dbt Core/Cloud. Discuss any complexities you've managed, such as model development, orchestration, testing, and documentation, as these are important skills for the Analytics Engineer role.

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Can you explain a time when you optimized a data workflow?

To effectively answer this question, share a specific example where you identified inefficiencies in a data workflow, the actions you took to optimize it, and the impact your changes had, especially in terms of performance and data reliability.

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How do you ensure the trustworthiness of data during your analysis?

Discuss your approach to writing tests and maintaining documentation for data models. Emphasize how you validate data integrity through medallion architecture, as well as any methods you employ to constantly monitor data quality.

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Describe your experience with cloud data platforms, specifically Snowflake.

When answering this, focus on your direct experience with Snowflake. Talk about the projects you've completed using the platform and how you utilized its features to enhance data querying and management, proving your expertise in cloud environments.

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How do you approach collaboration with cross-functional teams?

Share your experiences in collaborating with different teams, emphasizing clear communication and teamwork. Talk about how you’ve engaged with product, customer success, and leadership to align data models with business goals.

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What strategies do you use to manage deadlines in a fast-paced environment?

Provide insight into how you prioritize tasks and manage your time effectively. Discuss techniques you use, such as setting realistic goals, using project management tools, and communicating with your team to meet deadlines.

Join Rise to see the full answer
Can you explain your experience with writing SQL transformations?

Prepare to discuss your proficiency in SQL by providing examples of complex transformations you've written. Be ready to detail the scenarios in which you applied these skills and the outcomes they produced.

Join Rise to see the full answer
What do you think is the most important skill for an Analytics Engineer?

In responding to this question, you might mention analytical skills as crucial for deriving insights and solving problems. However, emphasize the importance of collaboration and communication skills for ensuring successful teamwork and stakeholder engagement.

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How do you handle feedback on your data models?

Share your openness to feedback and how you actively seek it from teammates and stakeholders. Discuss how you have made adjustments based on constructive criticism and the positive outcomes that resulted from these iterations.

Join Rise to see the full answer
What tools do you use for version control in your projects?

Describe your experience with git and how you apply version control best practices in your projects. Highlight the importance of maintaining a clean codebase and collaborative workflows through effective version control systems.

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Kalibri Labs is headquartered in Rockville, Maryland. Kalibri Labs is an analytics company that operates a platform to assist hotels to improve their profit contribution by predicting and evaluating performance net of acquisition costs.

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Full-time, remote
DATE POSTED
April 16, 2025

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