About the job
Our ideal candidate has an interest in AI/ML solutions, has experience collaborating across multi-disciplinary teams, and has demonstrated experience partnering with business leaders to deliver impactful assets and solutions.
What Will You Do
Work closely with team members and stakeholders to turn business problems into analytical projects, translated requirements, and solutions
Work cross-functionally with teams on data migration, translation, and organizational initiatives
Translate large volumes of raw, unstructured data into highly visual and easily digestible formats
Develop and manage data pipelines for predictive analytics modeling, model lifecycle management, and deployment (Extract-Load-Transform, ELT)
Recommend ways to improve data reliability, efficiency, and quality
Help create, maintain, and implement tools, libraries, and systems to increase the efficiency and scalability of the team
Develop and maintain proper controls and governance for data access
Communicate data-related challenges and help to prioritize resolutions based on alignment with organizational goals
Consult and assist consumers of XE managed data
What Will You Bring
Ability to critically analyze data, testing hypothesis, and validating data quality
Ability to problem solve and to test and implement new technologies and tools
Solid grasp of data systems and how they interact with each other
Exceptional analytical skills to detect the source and resolution of highly complex problems
Proficient Python programming skills are required and experience with Python-based analysis frameworks such as pandas, pyspark and pyarrow a plus
Experience with Starburst, Snowflake and other Cloud Data Warehousing / Data Lake preferred
Excellent data manipulation skills required, namely using SQL and the Python Scientific stack (pandas, numpy, sci-kit learn)
Experience extracting unstructured data from REST APIs, NoSQL databases, and object storage (Ceph/S3)
Experience with Linux system administration, shell scripting, and virtualization technology (containers) is required
Mastery of git (version control) and experience with versioning, merge request, review, etc. processes and techniques is required
Experience with distributed computing frameworks (eg., dask, pyspark) preferred
OpenShift application development and administration is a plus
Experience deploying applications using PaaS technologies (e.g,. OpenShift, Airflow) is a plus
Python coursePandasPysparkPytube+16
