Analytics Engineer

The Analytics engineer is a modern data team member that is responsible for modeling data to provide clean, accurate datasets. These datasets will feed data visualizations and reports for different users within the company. Their role entails transforming, testing, and documenting data. The role contributes to the organization’s strong drive to be at the forefront of using Artificial Intelligence (AI) in clinical trials to simplify data processing and discover imperceptible correlations.

Primary Responsibilities

• Model raw data into clean, tested, and reusable datasets to make it easier for business analysts and other stakeholders to view and understand data in a data warehouse or database.
• Maintaining data documentation to ensure that everyone on the team uses the same definitions and language. This involves providing identifiable and understandable descriptions of data as well as exposing them in a way for all consumers to easily find answers to their queries.
• Define certain metrics to be used and measures to be taken to guarantee data is accurate enough to fit operational and analytics needs.
• Work closely with Data Analysts and Business Intelligence Analysts to create tables and views that improve the dashboard performance and simplify build process.
• Building dashboards, graphs, charts, and reports using BI tools
• Follows Data Quality, Data Governance and Master Data Management Best Practices to enable the business to maintain clean and accurate data
• Engages with various internal cross-functional departments to develop and implement data tables, views, and metrics.
• Delivers high quality software tests and code documentation
• Contributes to the development of standard operating procedures for the use of artificial intelligence and data engineering within clinical trials
• Prototypes new ideas/technologies to create proof of concept and demos
• Adherence to all essential systems and processes that are required at SDC to maintain compliance to business and regulatory requirements
• Act as a resource for other team members for debugging, code reviews and other software development lifecycle activities

Requirements

• Fluency in SQL and parsing, manipulating, and converting data into tables and views.
• Familiarity with python data libraries (e.g.,pandas, dbt)
• Ability to work with database management tools (e.g., dbeaver, datagrip)
• Ability to do use git to handle version control.
• An understanding of modern RDBMS concepts (joins, indexes, views) and SQL syntax (group by, having), including experience with at least one modern RDBMS.
• Experience in the software development lifecycle.
• Ability to work with stakeholders to translate business requirements into clear technical specifications
• Ability to communicate effectively in writing and verbally.
• Ability to identify issues, present problems, and implement solutions
• Capability of communicating technical concepts clearly, concisely, and understandably to non-technical colleagues
• Good organizational and time management skills, with the ability to push forward multiple projects simultaneously
• Strong interpersonal communication and presentation skills

Education or Equivalent Experience

• Bachelor’s degree in a technical field with 2 years of technical experience with the last 2 years of SQL related experience being a Data Engineering centric role.

OR

• 3+ years in a technical role with the last 2 years being an Analytics centric role.