Support data eco-system via data Ingestion and Modelling, Operational Monitoring, Onboarding, Data Health, governance
Propose data engineering solutions to support different modelling strategies
Design, build and support healthy, automated, and repeatable data ingestion and processing pipelines
Raw data ingestion, cleansing, and data contracts
Design data models and data contracts
Monitor and maintain data quality, integrity, consistency
Help design and build scalable, reliable, and high-performance systems and environments
Effectively contribute to building the overall knowledge and expertise of the technical team
Participate in work and code reviews with the team
Take part in implementation and support of continuous integration and continuous delivery (CI/CD)
Work on systems to monitor system health, data quality and scientific performance
Implement data access-control for compliance with data governance policies
Contribute to technical documentation
Collaborate with developers, data analysts, data scientists and organizational leaders to identify opportunities for process improvements

Requirements

Minimum 3-year Cloud deployment experience (Azure preferred)
Minimum 3 years’ experience in relational and non-relational database technologies
Minimum 3-years’ experience supporting data science and analytics projects and/or infrastructure
Minimum 3-years building production grade ETL pipelines and Data Mesh and/or Data Bricks
Must be proficient in Python, SQL, PySpark
Experience working with Large Language Models (LLM) and Natural Language Processing (NLP) technologies
Experience working with graph databases, knowledge graphs, and their languages (e.g. GraphQL, Cypher)

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonSQLPySparkETL pipelinesData MeshData BricksLarge Language ModelsNatural Language Processinggraph databasesGraphQL

Soft Skills

collaborationcommunicationproblem-solvingteamworktechnical documentation