Senior Analytics Engineer

As a Senior Analytics Engineer at Ironclad, your responsibilities will include developing and optimizing our dbt infrastructure, designing high-quality and scalable data transformations, and maintaining consistent business logic across various datasets. You will also unify metrics and definitions across our data warehouse, mentor fellow team members, and collaborate with data engineering on design and transformation pipelines.

To qualify for the Senior Analytics Engineer role at Ironclad, you should have at least 5 years of experience in analytics, data engineering, or business intelligence engineering, along with a minimum of 2 years developing in dbt, ideally in a B2B SaaS context. Proficiency in SQL, experience with data modeling, and familiarity with tools like Segment, Fivetran, and BigQuery are also preferred.

Ironclad supports Senior Analytics Engineers by fostering a collaborative environment where mentoring and upskilling are encouraged. You'll have the opportunity to provide guidance through code reviews and foster a culture of learning while also ensuring best practices in dbt and data modeling are upheld across the team.

The base salary range for the Senior Analytics Engineer position at Ironclad is between $175,000 and $200,000. This range depends on various factors, including individual proficiency and performance. Additionally, Ironclad offers a competitive total rewards package that includes equity awards and comprehensive health benefits.

At Ironclad, the work culture values collaboration, inclusivity, and innovation. Senior Analytics Engineers work in a supportive environment surrounded by forward-thinking individuals. Our recognition as a Great Place to Work for four consecutive years highlights our commitment to creating a positive and engaging workplace for all employees.

In your response, emphasize specific projects where you've applied dbt to build data models or transform data pipelines. Describe challenges you faced and how you used dbt to solve them, showcasing your technical skills and problem-solving abilities.

Discuss methods you've implemented to monitor data quality, such as automated testing or governance processes. Share examples of how you've handled data discrepancies and ensured compliance, emphasizing the importance of data integrity in driving business decisions.

Describe your time management strategies, such as using project management tools or techniques like the Eisenhower Matrix. Highlight your ability to assess project impact and urgency, ensuring the most critical tasks receive your attention first.

Choose a specific project to discuss, detailing the objectives, stakeholders involved, challenges encountered, and the technology stack you used. Highlight measurable outcomes that positively affected the organization to demonstrate your effectiveness.

Share your philosophy on mentorship, including the importance of fostering a supportive learning environment. Provide examples of how you've guided junior engineers or analysts through code reviews, knowledge-sharing sessions, or supportive training.

Discuss your methods for simplifying complex ideas, such as using analogies, data visualizations, or clear documentation. Emphasize your ability to align technical insights with business needs and the value of effective communication in your role.

Highlight your proficiency in SQL, mentioning specific tasks like data extraction, modeling, or query optimization. Share examples of how your SQL skills have driven analytics projects or supported business decision-making by delivering key insights.

Reflect on a specific challenge you faced, detailing the context and the impact it had. Explain your problem-solving approach, the steps you took to rectify the issue, and what you learned from the experience to avoid similar setbacks in the future.

Discuss aspects like flexibility, performance, and maintainability. Explain how each component contributes to building data models that can efficiently handle growth and change, supporting the collaborative objectives of the cross-functional teams at Ironclad.

Share your strategies for professional development, such as following industry publications, participating in conferences, or engaging in online courses. Emphasize your commitment to continuous learning and how it enriches your contributions as a Senior Analytics Engineer.