Senior Data Engineer, Analytics

OVERVIEW & RESPONSIBILITIES

This role will be responsible for growing and optimizing the Studio’s data and data pipeline architecture, monitoring and running backend infrastructure, as well as automating data processes for the Global Analytics and Data Science team. We seek a candidate with a passion for data and technology, for optimization of data infrastructure, automation, and building pipelines from the ground up. As a Senior Data Engineer, you will be part of a multi-functional Global Analytics and Data Science team, collaborating closely with executives, data scientists, and data analysts on various data initiatives, infrastructure, and automation of data workflows. Are you a credible data pipeline builder and engineering aficionado who is dedicated to and excited by the prospect of optimizing, owning, and growing data architecture to support the Studio’s ongoing data projects?

• Build and maintain an efficient data pipeline architecture
• Assemble large, complex data sets that meet functional and non-functional business requirements
• Adjust infrastructure and pipelines to accommodate new data sources and business requirements, keeping the infrastructure agile and adaptable
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, and re-designing infrastructure for greater scalability
• Run the infrastructure required for optimal extraction, transformation, and loading (ETL) of data from a wide variety of data sources
• Collaborate with partners, technical and non-technical, to assist with data-related technical issues and support their data infrastructure needs
• Amalgamate with the team to strive for clean and germane data, and greater functionality and flexibility within the team’s data systems
• Author user documentation and artifacts around infrastructure-, automation-, and ingestion projects

BASIC QUALIFICATIONS:

• 3+ years of hands-on experience in a Data Engineering role, preferably in data engineering, complex data technologies, and cloud computing platforms with shown strength in the following platforms/tools or equivalents:
• STEM degree in Computer Science, Information Technology, Software Engineering, Data Engineering, Data Science, Mathematics, Physics, etc. or similar
• Object-oriented/object function scripting in: Python
• Other coding languages: PySpark, SQL
• Code Hosting Platform: GitHub
• Workflow Scheduling: Apache Airflow
• Containerization: Kubernetes
• CI / CD: Terraform
• Big Data Analytics Platform: Databricks
• Cloud Technologies: Google Cloud Platform and/or AWS
• Advanced SQL knowledge, query authoring, and perspicacity in relational databases
• Experience building, maintaining, and optimizing complex data pipelines, architectures, and datasets
• Experience cleaning, testing, and evaluating data quality from a wide-variety of ingestible data sources
• Design processes supporting data transformation, data edifice, metadata, dependency and workload management
• Experience monitoring backend infrastructure health and collaborating with appurtenant engineering teams, such as Cloud Governance to ensure data processes are uninterrupted and exhibit high quality standards
• Solid project management and organizational skills
• Experience supporting and working with multi-functional teams in a dynamic environment
• Strong verbal and written communications skills with both technical and non-technical collaborators
• Superb attention to detail

ADDITIONAL QUALIFICATIONS

• Involvement with and participation in: iterative agile environments; matrix organizational constellations; cloud governance and other backend adjacent engineering teams to monitor sound infrastructure and resources supporting production pipelines
• Experience with monitoring tools such as Grafana
• Data warehouses: Google BigQuery, Snowflake
• Open source automation server: Jenkins
• A lifelong learner who actively seeks out opportunities to acquire new skills, stay updated on industry trends, and be conducive to a milieu of innovation and intellectual curiosity

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