• Design, build, and maintain scalable data pipelines and workflows across modern cloud data platforms—Snowflake, Databricks, Microsoft Fabric, or equivalent • Implement ELT/ETL processes with a focus on data quality, performance, reliability, and maintainability • Assemble and transform large, complex datasets that meet both functional and non-functional business requirements • Build and optimize data models to support analytics, reporting, and AI/ML use cases • Work across cloud environments (AWS, Azure, GCP) and their native data services • Contribute to solution design discussions alongside architects; bring engineering-level perspective on feasibility, complexity, and implementation trade-offs • Help define data pipeline patterns, platform configurations, and engineering standards within the engagement • Identify opportunities to improve data infrastructure: automate manual processes, improve data delivery, redesign for greater scalability and performance • Build analytics tools and data products that surface actionable insights for clients across key business metrics • Support integration with BI and visualization tools (Power BI, Tableau, Looker, Qlik, or similar) • Ensure data products are well-documented, governed, and ready for downstream consumption • Participate in client discovery and requirements-gathering sessions; contribute an engineering-level perspective on feasibility, complexity, and implementation approach • Support pre-sales and scoping activities alongside Architects and Pre-Sales teams—help validate that proposed solutions are technically achievable before commitments are made • Engage directly with client technical teams throughout the engagement lifecycle; build credibility through engineering quality and clear communication • Work effectively across multiple client engagements at different stages of the implementation lifecycle • Collaborate with architects, solution owners, and client technical teams to deliver against agreed outcomes • Mentor junior data engineers; share knowledge and raise the engineering quality of the teams you work with • Communicate technical progress, blockers, and decisions clearly to both technical and non-technical stakeholders.

• Develop technical enablement content, including presentations, solution guides, white papers, workshops, labs, and training materials. • Design, build, and maintain product demonstrations that showcase customer challenges, technical capabilities, and business outcomes. • Support field sales, systems engineering, and channel teams by providing technical expertise and creating customer-facing content. • Deliver presentations at customer meetings, internal enablement sessions, partner events, and industry conferences. • Collaborate closely with Product Management, Engineering, Marketing, and regional field organizations to support product launches and strategic initiatives. • Stay current on emerging technologies and industry trends in data center networking, automation, AI, and cloud infrastructure. • Translate complex technical concepts into clear, compelling messaging for technical and executive audiences.

• Implement advanced data engineering solutions • Use agile methodologies and industry best practices • Plan and execute data integration strategies • Ensure data quality and security • Develop and implement ETL processes, creating documentation • Create management reports using Power BI

Role Description As a Senior Software Engineer on the Data Platform team, you will design, build, and own the foundational systems that generate, track, and serve key business and client success metrics across MNTN. You'll architect the infrastructure that turns billions of raw events into reliable, accessible data products, and you'll be a technical leader who helps shape how teams across engineering and operations build on top of that platform to explore and realize new opportunities. - Design and build scalable, reliable data platform services and infrastructure that power operations, analytics, and product features across MNTN. - Become a go-to expert on the MNTN ad platform and the data systems, pipelines, and processes that inform engineering and operations. - Architect and own ETL/ELT systems that transform billions of raw data points daily into high-quality, low-latency data available across databases and data warehouses. - Build the frameworks, tooling, and abstractions that let other engineers and teams self-serve data reliably and confidently. - Establish and enforce data quality, observability, and SLA standards including the visualization, reporting, and alerting needed to surface performance, data quality, trends, and opportunities. - Drive technical design and architecture decisions, weighing tradeoffs around scalability, cost, reliability, and maintainability. - Lead incident investigation and resolution for critical data systems, and improve the platform to prevent recurrence. - Mentor other engineers, raise the bar on code quality and engineering practices, and influence technical direction beyond your immediate team. Qualifications - 5+ years of software engineering experience, with a strong focus on data platforms, data infrastructure, or backend systems at scale. - Proven ability to design and build distributed, fault-tolerant systems and data pipelines from the ground up. - Strong programming skills in Python, Java, or Go, and solid software engineering fundamentals (algorithms, systems design, testing). - Deep experience with SQL, data modeling, and working with large, complex datasets. - Hands-on experience with data warehouse technologies and designing ETL/ELT architectures. - Experience with data processing frameworks such as Spark. - Proficiency with modern software tooling and practices: Git, CI/CD pipelines, Linux, and orchestration tools such as Airflow. - Experience building and operating systems in a cloud environment such as AWS, Azure, or GCP. - A track record of technical leadership driving architectural decisions, mentoring engineers, and partnering across teams. - Strong written and verbal communication skills, with the ability to convey complex technical topics to both technical and non-technical audiences. Benefits - 100% remote within the US - Flexible vacation policy - Annual vacation allowance for travel related expenses - Three-day weekend every month of the year - Competitive compensation - 100% healthcare coverage - 401k plan - Flexible Spending Account (FSA) for dependent, medical, and dental care - Access to coaching, therapy, and professional development