What is the Senior Data Engineer in Fixed Income team responsible for

• On the Multisector Fixed Income team at Franklin Templeton Investments, we utilize cutting edge technology and mathematics to consistently generate sector-leading risk-adjusted returns.

• We are thrilled to add a talented data engineer to our group in order to enhance data availability, visualization of model output and enable rapid model deployment to impact portfolio positioning.

• You will be encouraged to develop creative solutions in a challenging problem space given a healthy mix of autonomy as well as guidance from senior leaders. You will have the opportunity to influence a variety of business vectors, making tangible impact early and often.

What are the ongoing responsibilities of the Senior Data Engineer

• Develop key data pipelines from data sources to data warehouses

• Establish and grow data warehouses.

• Place AI/ML solutions in production using a variety of execution methodologies

• Collaborate with expert data scientists to develop models and ETL processes

• Develop long-term data architecture strategy

• Incorporate new enterprise tools to enhance data and model monitoring

• Establish data quality checks and best practices

What ideal qualifications, skills experience would help someone to be successful

• Bachelor s degree in computer science, information technology, engineering or equivalent

• 3-6 years of relevant experience

• Expert knowledge of Python 2.7 and 3.x

• Experience with model productionalization and data processing

• Experience with cloud infrastructure (GC, AWS, Databricks, etc.)

• Experience with PowerShell and Bash Scripting

• Experience with Snowflake, MySQL, and SQL (SQL ANSI standard)

• Experience with Linux environments

• Experience with git

• Familiarity with R/Shiny

Preferred Qualifications:

• Master s degree or higher computer/data science, stats, engineering, or equivalent

• Experience productionalizing Scikit-Learn, XGBoost, and enterprise AI models

• Experience with Python packages such as Pandas, Numpy, PySpark

• Experience working in the agile framework with tools such as JIRA and Confluence

• Experience building ML algorithms

• Experience implementing MLOps concept/frameworks

• Experience with Azure DevOps and StreamSets

• Familiarity with PHP/JavaScript/HTML/CSS