Senior Data Engineer

About the Role : As a Senior Data Engineer, you will be the lead architect and builder of the data backbone for our entire next-generation digital asset platform. Embedded within our "Agentic AI & Automation" squad, your mission is to design, build, and operate the scalable, reliable data pipelines and data lake that will power all analytics, business intelligence, and machine learning initiatives across the company.

This is a strategic, hands-on role for a seasoned data expert who thrives on building data platforms from the ground up. You will not just be moving data; you will be making fundamental architectural decisions about how we collect, store, process, and serve data in a highly secure and regulated financial environment. You will be the authority on data engineering best practices and will create the foundational systems that unlock the value of our data for our AI Engineers and the broader business.

Responsibilities : Must-Have :

Professional Experience : 10+ years of professional experience in data engineering, with a proven track record of architecting and building large-scale data platforms.

Expert Programming Skills : Expert-level proficiency in Python or Scala , along with mastery of SQL .

Big Data Technologies : Deep, hands-on experience with core big data technologies, including Apache Spark and a major cloud data warehouse (e.g., Snowflake, BigQuery, Redshift).

Stream Processing : Experience building and managing real-time data pipelines using stream-processing technologies like Apache Kafka , Flink, or Spark Streaming.

Data Orchestration : Proven expertise with workflow orchestration tools like Airflow .

Cloud Architecture : Extensive experience designing and building data solutions on a major cloud platform (AWS, GCP, or Azure).

Data Modeling : A strong background in data modeling and data architecture for analytical systems.

Nice-to-Have (Highly Desirable) :

FinTech / Crypto Domain : Experience building data platforms in a financial services or cryptocurrency environment is a massive plus.

Infrastructure as Code : Experience with Terraform for managing data infrastructure.

Kubernetes : Familiarity with deploying data workloads on Kubernetes.

Data Governance Platforms : Experience with data cataloging and governance tools.