Senior Data Infrastructure Engineer

About us

Xpend Marketing builds advanced marketing solutions that help brands scale fast. We work with leading companies in high-performance industries, supporting their growth across the entire funnel - from acquisition to retention. Our team specializes in performance marketing, paid social, and large-scale campaign management, operating across global markets and high budgets.

With a strong focus on data, speed, and continuous optimization, we enable our partners to launch, test, and scale campaigns that drive real results.

We are looking for a Senior Data Infrastructure Engineer to lead the design, build, and optimization of our data platform. This role is ideal for someone with hands-on experience building data lakes from scratch, working with modern cloud-based data technologies, and handling data at scale. You will play a key role in shaping our data architecture, ensuring high performance, cost efficiency, and reliability across complex data pipelines.

Key Responsibilities

• Design and build a data lake / data platform from the ground up using modern technologies such as Snowflake, Databricks, or similar platforms
• Architect and maintain scalable, reliable, and efficient data infrastructure
• Develop and optimize large-scale data pipelines for batch and/or streaming use cases
• Continuously improve performance, cost efficiency, and scalability of data systems
• Work with complex data workflows, AI models, transformations, and orchestration processes
• Collaborate closely with data engineers, analytics, data science and product teams to support business needs
• Apply best practices in data modeling, monitoring, security, and governance

Requirements

• 5+ years of experience in data engineering / data infrastructure roles
• Proven experience building a data lake or modern data platform from scratch
• Strong understanding of data at scale, including performance tuning, cost optimization, and system design
• Hands-on experience with platforms such as Snowflake, Databricks, BigQuery, Redshift, or similar
• Strong programming skills in Python
• Experience with Apache Spark (PySpark preferred)
• Solid understanding of distributed systems and cloud-based data architectures
• Experience with complex data pipelines and ETL/ELT processes

Nice to Have

• Experience with cloud providers (AWS, GCP, or Azure)
• Familiarity with data orchestration tools (Airflow, Dagster, etc.)
• Knowledge of data governance, security, and access control
• Experience supporting analytics, BI, or machine learning workloads

What We Offer

• Opportunity to design and own a modern data platform end-to-end
• Work on large-scale, high-impact data challenges
• Collaborative, professional engineering environment
• Competitive compensation and benefits