Job description

About the Role We’re looking for a highly skilled Senior Data Architect to join our client within the financial services sector. This is a fantastic opportunity for someone to work on large-scale data platforms and deliver production-ready machine learning solutions. What's in it for you Work at a fast-growing financial services firm There is the option for remote work if needed, but they ideally want someone to come onsite for 1 day a week in offices in Boston or NY Lead enterprise data projects 10% Bonus and Stock Options Key Responsibilities Design, build, and optimise scalable data pipelines using Databricks, PySpark and SQL. Work with modern cloud technologies — primarily Azure and Snowflake. Collaborate closely with data scientists, engineers, and business stakeholders to deliver high-quality, production-grade solutions. Troubleshoot performance issues and ensure quality, security and compliance in line with financial services regulations. Implement robust ML Ops practices, ensuring smooth deployment and monitoring of machine learning models. Must-Haves Advanced SQL experience, including performance tuning. Expertise in working with Snowflake data warehousing or Azure Data Lakes. Previous experience working in the financial services sector (banking, insurance, fintech or similar). Nice to Haves Solid understanding of ML Ops processes, tools, and model lifecycle management. Strong programming skills in Python. Hands-on experience with Databricks and PySpark.

Requirements

Must-haves

We’re looking for a highly skilled Senior Data Architect to join our client within the financial services sector.
This is a fantastic opportunity for someone to work on large-scale data platforms and deliver production-ready machine learning solutions.
Design, build, and optimise scalable data pipelines using Databricks, PySpark and SQL.
Work with modern cloud technologies — primarily Azure and Snowflake.
Collaborate closely with data scientists, engineers, and business stakeholders to deliver high-quality, production-grade solutions.
Troubleshoot performance issues and ensure quality, security and compliance in line with financial services regulations.
Implement robust ML Ops practices, ensuring smooth deployment and monitoring of machine learning models.
Advanced SQL experience, including performance tuning.
Expertise in working with Snowflake data warehousing or Azure Data Lakes.
Previous experience working in the financial services sector (banking, insurance, fintech or similar).

Nice-to-haves

Solid understanding of ML Ops processes, tools, and model lifecycle management.
Strong programming skills in Python.
Hands-on experience with Databricks and PySpark.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningsqlazuremlpython

Platform: careers-page
Effort: medium