Lead Analytics Engineer
2 weeks ago
Position Overview:
The role of the Senior Analytics Engineer involves a flexible work arrangement, allowing for collaboration with various Client locations. The position entails a significant on-site presence to foster teamwork and project execution.
Essential Skills:
- Proficient in SQL with over 5 years of experience
- At least 2 years of hands-on experience with dbt
- Extensive background (5+ years) in relational database management
- A Master's degree in Computer Science, Chemical Engineering, Biostatistics, or a related field with a minimum of 6 years of industry experience, or a PhD in a similar discipline with at least 3 years of relevant experience
- Intermediate proficiency in Python programming
- Experience in data visualization tools such as Tableau or similar
Key Responsibilities:
- Conduct data engineering tasks, including preprocessing, exploratory data analysis, and model development by engaging with diverse databases
- Oversee the ingestion, integration, and dissemination of data across various platforms
- Ensure the maintenance of data integrity and adherence to clean data principles
- Lead team code reviews and enhance programming practices within the team
- Independently manage and coordinate analytics projects across multiple departments and with cross-functional stakeholders
- Collaborate effectively with a global team, communicating across different time zones
- Regularly update team members and collaborate on project deliverables
- Accountable for leading and documenting analytics User Requirement Specifications (URS) and User Acceptance Testing (UAT)
- Guide and engage colleagues involved in data-related tasks
- Design and implement digital solutions that facilitate access to analytics and data
- Work closely with subject matter experts to extract insights and enhance manufacturing data transformation initiatives
- Exhibit strong teamwork and collaboration skills across functions
- Utilize supervised or unsupervised learning techniques to derive insights from extensive unlabeled data
- Experience in processing unstructured text data
- Maintain lifecycle management of code through version control and associated repositories
- Create high-quality analytical and statistical models, insights, and visualizations to support decision-making in manufacturing operations
- Document all technical work comprehensively, both within and outside formal document management systems
- Independently develop code and analytical models to automate data transformation and analysis processes
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