Mural is a visual work platform designed to enhance collaboration, productivity, and innovation for teams. It offers a secure, AI-powered environment for planning, meetings, and project work, aiming…
Mural is a visual work platform designed to enhance collaboration, productivity, and innovation for teams. It offers a secure, AI-powered environment for planning, meetings, and project work, aiming…
Customers: Enterprise-focused; claimed adoption by over 50% of the Fortune 100
Funding: Raised multiple venture rounds totaling about $193.63M (including Series A/B/C)
Founders: Co-founded by Mariano Suárez-Battan and Agustín Soler
Company Overview
Problem Domain
Team collaboration, remote facilitation, ideation and alignment across distributed organizations.
Industry
Collaboration software / productivity
Funding Track Record
Seed- 2016-07-07
1350000.00
Seed round reported at $1.35M with investors including Alta Ventures, NXTP Labs, Intel Capital and Collaborative Fund
Series A- 2020-01-27
23000000.00
Series B- 2020-08-25
118000000.00
Series C- 2021-07-20
50000000.00
Series C reported at $50M; company valuation reported above $2B
Investor Signal
“Backed by growth and venture investors including Insight Partners, Tiger Global, Radian Capital, Gradient Ventures, Intel Capital and others”
Founders
What we do
Join the Team
Senior DataOps Engineer
On-SiteMX
On-Site • MX
About The Team
The Data Engineering team at Mural builds scalable, high-performance systems that transform complex data into actionable insights. We power internal analytics and user-facing features, supporting critical products powered by AI/Machine Learning, such as Customer Insights, Personalization, Reporting APIs, and Audit Logs. Our work integrates diverse data sources, optimizes core data models, and ensures seamless access across the organization. Success is measured not only by system reliability and scalability, but also by the business impact we deliver—enabling users to make informed decisions and driving overall customer success.
YOUR MISSION
As a Senior Data Engineer, you will be instrumental in shaping the future of our data platform. You will work with a global, remote-first team to build, scale, and optimize our data infrastructure using cutting-edge tools like Databricks, Spark, Terraform, and cloud platforms (AWS/Azure). You will collaborate closely with cross-functional teams to ensure the platform is secure, efficient, and continuously evolving. Your work will empower teams to access the data they need, drive insights, and optimize business outcomes.
What You'll Do
Build, scale, and optimize the data platform using Databricks, Spark, and various data integration tools to ensure high performance, reliability, and cost efficiency.
Design and maintain robust data pipelines with Airflow, Fivetran, DBT, Segment, and automate infrastructure using Terraform to enhance operational readiness, security, and governance.
Develop and maintain the infrastructure and automation needed to support MLOps practices, including model deployment pipelines, monitoring frameworks, and retraining automation.
Use AI tools as a part of your fundamental workflows
What You'll Bring
Equal Opportunity
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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Prototype, implement, and maintain team projects and features, serving as a technical expert, mentor, and leader
Build flexible and maintainable solutions while being accountable for quality, performance, and reliability
Elevate the team’s skills and knowledge by participating in technical designs and talks and reviewing and helping improve your and your colleague’s code
Contribute to constantly improving the team’s processes and best practices
4+ years of hands-on experience in Data Engineering, with a strong focus on building and optimizing data platforms and cloud platforms.
Expertise in designing and building distributed systems and data pipelines, focusing on data integration, transformation, and processing using tools like Astronomer, Fivetran, DBT, and Segment, with a focus on both structured and unstructured data.
Proficiency in Python, Scala, SQL, and Spark to develop scalable data pipelines, automate data workflows.
Solid understanding of cloud infrastructure (AWS/Azure), data platforms (Databricks, Snowflake, Redshift) with hands-on experience in Terraform to automate cloud resource management (e.g., VPCs, subnets).
Passion for performance tuning, cost optimization, and ensuring efficient resource usage across the data platform.
An outcome-oriented and highly-experimental interest in AI-driven development practices
Experience with data governance, security practices, and compliance (e.g., SOC II) to maintain data integrity and privacy.
Experience learning new technologies, platforms, stacks, and coming up to speed quickly on large codebases
Emotional intelligence with collaboration and listening skills that encourage innovative solutions and diverse perspectives
Experience working in a rapid-growth or startup environment
Excellent communication skills and the ability to collaborate with distributed teams across time zones, ensuring alignment and success in a fast-paced environment.
