Javen Technologies
JOB DESCRIPTION
Squad:
Customer Recommendation and Insights squad in the Data Insights Tribe Required:
In office 4 days a week minimum (Monday-Wednesday, Friday)
We're hiring a
Data Engineer
to join our newly launched Machine Learning Data Enablement team at ***. This team is focused on building high-quality, scalable data pipelines that power machine learning models across the enterprise, deployed in AWS SageMaker.
We're looking for an early-career professional who's excited to grow in a hands-on data engineering role. Ideal candidates will have experience working on
machine learning-related projects
or have partnered with
data science teams
to support model development and deployment - and have a strong interest in enabling ML workflows through robust data infrastructure.
You'll work closely with data scientists and ML engineers to deliver curated, production-ready datasets and help shape how machine learning data is delivered across the bank. You should have solid SQL and Python skills, a collaborative mindset, and a strong interest in modern data tooling. Experience with Snowflake, dbt, or cloud data platforms is a strong plus. Familiarity with ML tools like SageMaker or Databricks is helpful but not required - we're happy to help you learn.
This is a hands-on role with high visibility and high impact. You'll be joining a team at the ground level, helping to define how data powers machine learning at scale.
Customer Recommendation and Insights squad in the Data Insights Tribe Required:
In office 4 days a week minimum (Monday-Wednesday, Friday)
We're hiring a
Data Engineer
to join our newly launched Machine Learning Data Enablement team at ***. This team is focused on building high-quality, scalable data pipelines that power machine learning models across the enterprise, deployed in AWS SageMaker.
We're looking for an early-career professional who's excited to grow in a hands-on data engineering role. Ideal candidates will have experience working on
machine learning-related projects
or have partnered with
data science teams
to support model development and deployment - and have a strong interest in enabling ML workflows through robust data infrastructure.
You'll work closely with data scientists and ML engineers to deliver curated, production-ready datasets and help shape how machine learning data is delivered across the bank. You should have solid SQL and Python skills, a collaborative mindset, and a strong interest in modern data tooling. Experience with Snowflake, dbt, or cloud data platforms is a strong plus. Familiarity with ML tools like SageMaker or Databricks is helpful but not required - we're happy to help you learn.
This is a hands-on role with high visibility and high impact. You'll be joining a team at the ground level, helping to define how data powers machine learning at scale.