About the Role
We are looking for a highly experienced Senior Data Engineer to join our growing AI technology team. In this role, you will design, build, and scale the data infrastructure that powers our AI/ML platforms, products, analytics, and intelligent applications.
The ideal candidate brings 10+ years of Data Engineering experience, including 3+ years of hands-on Snowflake experience, along with strong expertise in Apache Spark, Apache Airflow, Python/Scala, SQL, AWS, and modern data architecture.
You will work closely with AI/ML engineers, software engineers, data scientists, architects, and product teams to build reliable and scalable data systems in a fast-paced startup environment.
Key Responsibilities
Design, develop, and maintain scalable data platforms supporting AI/ML and data-intensive applications.
Build high-performance ETL/ELT pipelines for large volumes of structured and semi-structured data.
Develop and optimize data processing solutions using Snowflake, Apache Spark, and Apache Airflow.
Build reliable data ingestion and transformation pipelines from multiple sources.
Design data models and architectures optimized for analytics, machine learning, and AI workloads.
Develop cloud-based data solutions using AWS and Amazon S3.
Optimize Snowflake databases, SQL queries, data models, and data pipelines for performance and scalability.
Implement data orchestration, scheduling, monitoring, and workflow automation using Apache Airflow.
Work closely with AI/ML engineers and data scientists to provide high-quality datasets for model development, training, evaluation, and production workloads.
Support real-time and batch data processing requirements as needed.
Implement data quality, validation, monitoring, governance, and observability practices.
Build and maintain CI/CD pipelines for data engineering applications and infrastructure.
Use Git and modern software engineering practices for development and deployment.
Troubleshoot complex data pipeline and production issues.
Contribute to the evolution of the company's data architecture as the AI platform scales.
Collaborate with engineering, product, AI/ML, and business teams to translate requirements into scalable technical solutions.
Work effectively in a fast-paced startup environment, taking ownership of projects from design through production.
Required Qualifications
10+ years of professional experience in Data Engineering.
3+ years of hands-on experience with Snowflake.
Strong experience designing and developing enterprise-scale data pipelines and data platforms.
Strong hands-on experience with Apache Spark.
Strong hands-on experience with Apache Airflow or equivalent orchestration technologies.
Advanced SQL skills and strong programming experience with Python and/or Scala.
Strong understanding of ETL/ELT, data modeling, data integration, and data architecture.
Experience working with both structured and semi-structured data.
Strong experience with AWS cloud services, particularly Amazon S3.
Experience designing data solutions for large-scale and high-volume workloads.
Experience with Git, version control, and CI/CD pipelines.
Strong understanding of data quality, monitoring, and pipeline reliability.
Excellent problem-solving and analytical skills.
Strong communication and collaboration skills.
Ability to work independently and take ownership in a rapidly changing startup environment.
Bachelor's degree in computer science, Engineering, Information Technology, or a related field.
Must be authorized to work for any U.S. company without requiring visa sponsorship or transfer now or in the future.
Preferred Qualifications
Experience working in an AI/ML, SaaS, cloud technology, or high-growth startup environment.
Experience building data infrastructure supporting machine learning or generative AI applications.
Experience with large-scale distributed data processing.
Experience with Apache Kafka or other streaming technologies.
Experience with modern data lake/data warehouse architectures.
Experience with Snowflake performance optimization and cost management.
Experience working closely with Data Scientists, ML Engineers, and AI Engineers.
Experience building highly scalable data platforms from an early-stage environment.

What You'll Bring
Strong ownership and a startup mindset.
Ability to solve complex data problems with practical and scalable solutions.
Passion for building infrastructure that enables AI and machine learning innovation.
Ability to work across engineering, AI/ML, product, and business teams.
Comfortable working in a rapidly evolving environment where priorities can change quickly.
Strong focus on reliability, scalability, performance, and engineering quality.

Apply now

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