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Job Location: Hyderabad/Secunderabad
What is the Senior Data Engineer in Fixed Income team responsible for
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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.
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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.
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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
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Develop key data pipelines from data sources to data warehouses
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Establish and grow data warehouses.
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Place AI/ML solutions in production using a variety of execution methodologies
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Collaborate with expert data scientists to develop models and ETL processes
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Develop long-term data architecture strategy
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Incorporate new enterprise tools to enhance data and model monitoring
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Establish data quality checks and best practices
What ideal qualifications, skills experience would help someone to be successful
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Bachelor s degree in computer science, information technology, engineering or equivalent
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3-6 years of relevant experience
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Expert knowledge of Python 2.7 and 3.x
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Experience with model productionalization and data processing
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Experience with cloud infrastructure (GC, AWS, Databricks, etc.)
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Experience with PowerShell and Bash Scripting
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Experience with Snowflake, MySQL, and SQL (SQL ANSI standard)
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Experience with Linux environments
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Experience with git
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Familiarity with R/Shiny
Preferred Qualifications:
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Master s degree or higher computer/data science, stats, engineering, or equivalent
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Experience productionalizing Scikit-Learn, XGBoost, and enterprise AI models
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Experience with Python packages such as Pandas, Numpy, PySpark
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Experience working in the agile framework with tools such as JIRA and Confluence
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Experience building ML algorithms
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Experience implementing MLOps concept/frameworks
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Experience with Azure DevOps and StreamSets
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Familiarity with PHP/JavaScript/HTML/CSS
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