FAQs
What is the primary responsibility of the Senior Data Engineer, Analytics?
The primary responsibility is to grow and optimize the Studio’s data and data pipeline architecture, monitor and run backend infrastructure, and automate data processes for the Global Analytics and Data Science team.
What qualifications are required for this role?
A STEM degree in Computer Science, Information Technology, Software Engineering, Data Engineering, Data Science, Mathematics, Physics, or a similar field is required, along with 3+ years of hands-on experience in data engineering and complex data technologies.
What programming languages and tools should a candidate be familiar with?
Candidates should have experience with Python, PySpark, SQL, GitHub, Apache Airflow, Kubernetes or Docker, Terraform, Databricks, as well as cloud technologies like Google Cloud Platform and/or AWS.
What type of experience is preferred for this role?
Preferred experience includes building, maintaining, and optimizing complex data pipelines, cleaning and evaluating data quality, monitoring backend infrastructure health, and working with multi-functional teams in a dynamic environment.
Are there any specific cloud technologies or platforms that the candidate should have experience with?
Yes, the candidate should have experience with Google Cloud Platform and/or AWS, along with familiarity with data warehouses such as Google BigQuery and Snowflake.
What are the expectations regarding collaboration in this position?
The candidate will collaborate closely with both technical and non-technical partners, including executives, data scientists, and data analysts, to assist with data-related technical issues and support data infrastructure needs.
What kind of project management skills are necessary for this role?
Strong project management and organizational skills are necessary, along with the ability to communicate effectively with both technical and non-technical collaborators.
What additional qualities are preferred beyond the basic qualifications?
Preferred qualities include involvement in agile environments, experience with monitoring tools like Grafana, knowledge of open-source automation servers such as Jenkins, and a commitment to lifelong learning and staying updated on industry trends.
What is the importance of data quality in this role?
Maintaining high data quality is crucial as it supports clean and relevant data for analytics, ultimately enhancing the effectiveness and accuracy of data-driven decision-making processes within the Studio.
Will the Senior Data Engineer be responsible for documentation?
Yes, the role includes authoring user documentation and artifacts related to infrastructure, automation, and ingestion projects.
What does the process of automating data processes involve?
It involves identifying, designing, and implementing internal process improvements, optimizing data delivery, and redesigning infrastructure to enhance scalability and efficiency.