Business Intelligence Engineer II, Ops Finance - London, United Kingdom - Amazon UK Services Ltd.

Description

Does data platform standardization and data engineering automation driving analytics and reporting excite you? Do you thrive in a fast paced, ambiguous environment, enjoy transforming data into actionable recommendations, implement data governance standard practices, define best practices of data access, quality, consistency and innovate to deliver world-class business intelligence? If yes, then look no further The Worldwide Operations Finance Standardization & Automation (SnA) team is looking to hire a focused & customer-centric Business Intelligence Engineer to establish a standardized data platform with clean, reliable and accessible data feeds allowing Operations Finance customers to trust the data, technology and the tools and help become more data aware and make data-driven business decisions.

The ideal candidate is a seasoned data professional with strong bias for action, data modeling, ETL, SQL and scripting skills.

In this role you will help identify complex business problems, identify opportunities and implement solutions to improve Operations Finance facing systems, processes and tools.

The successful candidate will be a self-starter, quick learner, comfortable with ambiguity, result oriented with strong attention to detail, insists on high standards, shows ability in decision making and ready to adapt in a fast paced business changing circumstances.

You will be responsible for setting data architecture design, data modeling standards, building complex data pipelines, building and maintaining data lake, identify complex/abstract problems and building products in NAWS tech-stack, CI/CD pipeline.

Further, you will help automate processes by developing deep-dive tools, UIs, metrics, and dashboards to communicate these insights in real time to the business teams.

Successful members of this team collaborate effectively with business customers, product managers, cross-functional data management teams to solve problems, and implement new solutions.

• Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc.
• Experience with data visualization using Tableau, Quicksight, or similar tools
• Experience with data modeling, warehousing and building ETL pipelines
• Experience in Statistical Analysis packages such as R, SAS and Matlab
• Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
• Experience with SQL
• Experience in the data/BI space

• Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
• Experience in data mining, ETL, etc. and using databases in a business environment with largescale, complex datasets