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Analytics Engineer

Data is at the core of modern business, yet many teams struggle with its overwhelming volume and complexity. At Atlan, we’re changing that. As the world’s first active metadata platform, we help organisations transform data chaos into clarity and seamless collaboration.

From Fortune 500 leaders to hyper-growth startups, from automotive innovators redefining mobility to healthcare organisations saving lives, and from Wall Street powerhouses to Silicon Valley trailblazers — we empower ambitious teams across industries to unlock the full potential of their data.

Recognised as leaders by Gartner and Forrester and backed by Insight Partners, Atlan is at the forefront of reimagining how humans and data work together. Joining us means becoming part of a movement to shape a future where data drives extraordinary outcomes.

Why is this role important for us?

At Atlan, we believe the future belongs to the humans of data. To make that future a reality and accelerate our journey towards becoming an AI native company, we need a robust, reliable, and well-understood data estate. This Analytics Engineer role is absolutely critical; you will be the champion and owner of that estate. You won't just be managing data; you'll be transforming it into high-quality, trustworthy assets that empower our teams to make faster decisions, drive significant impact, and innovate rapidly. You are the crucial link ensuring our data fuels our growth.

What is your mission?

Your mission is to build and own world-class data foundations for Atlan. You will:

  1. Design, build, and manage robust data transformation pipelines.

  2. Turn raw data into clean, reliable assets using SQL and modern data transformation tools (like dbt).

  3. Model data effectively within our Snowflake warehouse. You will ensure data quality through strong testing practices.

  4. Identify what tools to adopt and what to discard as the modern data stack evolves with AI.

  5. Collaborate closely with teams across Atlan, delivering the data needed to drive decisions and power our AI future.

What makes you an ideal match?

We're looking for someone passionate about data's potential, skilled in building robust solutions, and excited to collaborate in a dynamic environment. Here’s what success looks like in this role:

  1. Expertise in Data Transformation & Modeling: You have strong hands-on experience designing, building, and maintaining reliable data transformation pipelines and scalable data models using expert SQL, modern transformation tools (like dbt), and cloud data warehouses (like Snowflake). Understanding modern data integration patterns (ETL/ELT tools like Fivetran) is key.

  2. Commitment to Data Quality & Reliability: Building trust in data is paramount. You ensure accuracy and reliability through rigorous testing, meticulous attention to detail, and collaborative development practices using tools like Git.

  3. Strong Problem-Solving Skills: You enjoy tackling complex data challenges, diagnosing issues, and translating ambiguous business needs into effective, practical technical solutions.

  4. Excellent Collaboration & Communication: You thrive working cross-functionally, building strong relationships, and explaining technical concepts clearly to diverse audiences, from engineers to business stakeholders.

  5. Deep Sense of Ownership: You take initiative and demonstrate end-to-end ownership of your work, feeling responsible for the quality, impact, and continuous improvement of the data assets you create.

  6. Passion for Enabling Insights: You're motivated by empowering others with data. Experience leveraging BI tools (especially Sigma) to visualize data and deliver actionable insights is highly valued.

  7. AI Ready: While you don’t need to be an AI expert, you need to be exploring the future of AI on analytics, data engineering and business intelligence and ready to make decisions that lay the groundwork for an AI centric data estate.

Why Atlan for You?

At Atlan, we believe the future belongs to the humans of data. From curing diseases to advancing space exploration, data teams are powering humanity's greatest achievements. Yet, working with data can be chaotic—our mission is to transform that experience. We're reimagining how data teams collaborate by building the home they deserve, enabling them to create winning data cultures and drive meaningful progress.

Joining Atlan means:

  1. Ownership from Day One: Whether you're an intern or a full-time teammate, you’ll own impactful projects, chart your growth, and collaborate with some of the best minds in the industry.

  2. Limitless Opportunities: At Atlan, your growth has no boundaries. If you’re ready to take initiative, the sky’s the limit.

  3. A Global Data Community: We’re deeply embedded in the modern data stack, contributing to open-source projects, sponsoring meet-ups, and empowering team members to grow through conferences and learning opportunities.

As a fast-growing, fully remote company trusted by global leaders like Cisco, Nasdaq, and HubSpot, we’re creating a category-defining platform for data and AI governance. Backed by top investors, we’ve achieved 7X revenue growth in two years and are building a talented team spanning 15+ countries.

If you’re ready to do your life’s best work and help shape the future of data collaboration, join Atlan and become part of a mission to empower the humans of data to achieve more, together.

We are an equal opportunity employer
At Atlan, we’re committed to helping data teams do their lives’ best work. We believe that diversity and authenticity are the cornerstones of innovation, and by embracing varied perspectives and experiences, we can create a workplace where everyone thrives. Atlan is proud to be an equal opportunity employer and does not discriminate based on race, color, religion, national origin, age, disability, sex, gender identity or expression, sexual orientation, marital status, military or veteran status, or any other characteristic protected by law.

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CEO of Atlan
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Prukalpa Sankar and Varun Banka
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What You Should Know About Analytics Engineer, Atlan

As an Analytics Engineer at Atlan, you're stepping into an exciting role that sits at the intersection of data and innovation. Our mission is to transform data chaos into clarity, and we believe that empowering people with data is the key to unlocking extraordinary outcomes. In this role, you'll design and manage robust data transformation pipelines, turning raw information into reliable assets that accelerate decision-making and drive impactful changes across the organization. Utilizing SQL and modern tools like dbt, you'll build scalable data models within our Snowflake warehouse, ensuring high data quality through thorough testing practices. We're looking for someone who relishes the challenge of problem-solving and can collaborate seamlessly with teams across Atlan. Communication is vital, as you'll be detailing complex technical concepts to a diverse audience. Your ability to adopt new tools as the data landscape evolves will be crucial in our quest to become an AI-native company. If you are passionate about data and thrive in a dynamic environment where you can take ownership of meaningful projects, then Atlan is the right place for you. You'll be part of a global community that's pushing the boundaries of what’s possible with data, working alongside industry leaders and contributing to exciting advancements in both data analytics and AI. Join us as we empower data teams to create winning data cultures and shape the future of collaboration!

Frequently Asked Questions (FAQs) for Analytics Engineer Role at Atlan
What are the main responsibilities of an Analytics Engineer at Atlan?

The primary responsibilities of an Analytics Engineer at Atlan include designing, building, and managing robust data transformation pipelines. You'll be responsible for turning raw data into clean, reliable assets using SQL and modern tools like dbt, effectively modeling data within our Snowflake warehouse while ensuring data quality through rigorous testing practices.

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What qualifications are required for the Analytics Engineer position at Atlan?

Atlan is looking for candidates with strong hands-on experience in data transformation and modeling, specifically using SQL, modern transformation tools like dbt, and cloud data warehouses such as Snowflake. A commitment to data quality, problem-solving skills, and excellent communication abilities are also essential for success in this role.

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How can an Analytics Engineer at Atlan contribute to the company's AI future?

As an Analytics Engineer at Atlan, you will help lay the groundwork for an AI-centric data estate by ensuring that the data is clean, reliable, and accessible. By collaborating with teams and utilizing your skills in data transformation and modeling, you'll contribute valuable insights that support the integration of AI in decision-making processes.

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What does teamwork look like for an Analytics Engineer at Atlan?

At Atlan, teamwork for an Analytics Engineer involves close collaboration with various teams across the organization. You will work with cross-functional teams to provide the data needed for decision-making, ensuring clear communication and relationship-building skills as you explain technical concepts in a way that resonates with both engineers and business stakeholders.

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What makes the Analytics Engineer position at Atlan unique?

The role of Analytics Engineer at Atlan is unique due to its focus on transforming chaotic data into actionable insights while being part of a global movement that is reimagining data collaboration. You'll have the opportunity to take ownership of impactful projects from day one and be supported by a community that emphasizes growth, diversity, and creative approaches to problem-solving.

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Common Interview Questions for Analytics Engineer
Can you describe your experience with SQL and data transformation tools in your previous roles?

In your answer, focus on specific examples of how you've used SQL to build data models and transformation pipelines. Highlight any tools like dbt that you've worked with and illustrate the outcomes of your efforts, such as efficiency gains or improved data quality.

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How do you ensure data quality in your data pipelines?

Discuss your approach to data quality, mentioning techniques like thorough testing, validation checks, and your attention to detail. Provide examples of situations where you identified and resolved data quality issues to enhance trust in your datasets.

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Can you give an example of a complex data problem you solved?

Choose a specific incident where you faced a challenging data problem and explain your thought process, the steps you took to address it, and the successful outcome. This demonstrates your problem-solving skills effectively.

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What experience do you have working in a cross-functional team?

Provide examples of past collaborative experiences where you liaised with different departments. Highlight the importance of clarity in communication and how your contributions supported the team in achieving common goals.

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What modern data integration patterns are you familiar with?

Be specific about the tools and patterns you have experience with, such as ETL/ELT processes, and describe how you've implemented these strategies in your work to deliver impactful data solutions.

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How do you stay updated with the latest trends in data analytics and engineering?

Share your strategies for staying informed about industry trends, such as following influential blogs, attending webinars, or participating in forums, which illustrate your commitment to continuous learning and professional development.

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What roles have you played in your previous projects as an Analytics Engineer?

Discuss specific roles you have played, including ownership of particular projects or initiatives, and how those experiences have prepared you for the responsibilities at Atlan.

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Can you explain a time when you had to communicate complex data findings to a non-technical audience?

Provide an example where you successfully translated technical data insights into terms that were easily comprehensible for non-technical stakeholders. Emphasize your communication skills and the tools you used for visual storytelling.

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What motivates you to work in the field of data?

Discuss your passion for data and how you see its potential to drive decision-making and innovation. Connect this to your desire to empower organizations and individuals through quality data solutions.

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How do you approach adopting new tools in your data workflow?

Explain your criteria for evaluating new tools and how you assess their benefits versus costs. Emphasize your willingness to experiment with innovative solutions to enhance your data engineering practices.

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DATE POSTED
April 17, 2025

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