Data Analytics Engineer

Data/Analytics Engineer Job Description
The Data/Analytics Engineering team empowers data-driven decision-making by developing and maintaining a robust data analytics platform to provide accurate, comprehensive, and actionable insights across the organization. As a Data/Analytics Engineer, you will bridge the gap between data engineering and data analysis, focusing on transforming raw data into analytics-ready datasets and creating efficient, scalable data models.
Responsibilities:
This role will be responsible for:

• Partnering with Data Engineering, Data Science, and Product teams to ensure data is transformed, modeled, and ready for analysis
• Managing data transformation pipelines that provide clean, well-documented datasets for analysis
• Implementing data quality checks and monitoring to ensure the reliability of analytics outputs
• Supporting ad-hoc data requests from internal/external clients for business continuity and analytics needs
• Documenting data lineage, business logic, and data models
• Continuously learning and sharing knowledge with the team and larger Data organization

Requirements for the Role

• Bachelor's degree in Computer Science, Statistics, or a closely related field, or equivalent experience
• 2+ years of experience in data analytics, business intelligence, or related field
• Strong proficiency in SQL and experience with modern data warehouses (e.g., Snowflake, BigQuery, Redshift)
• Proficiency in Python for data analysis and manipulation
• Solid understanding of data modeling concepts (e.g., dimensional modeling, star schemas)
• Experience with version control systems (e.g., Git) and collaborative development practices

Recommended but not required abilities:

• Experience with cloud platforms (e.g., Google Cloud Platform, AWS, Azure)
• Experience with real-time analytics or streaming data processing
• Familiarity with data governance and data catalog tools
• Understanding of statistical concepts and machine learning basics
• Top-tier communication skills:
• Ability to translate business requirements into technical specifications
• Experience in communicating complex data concepts to non-technical audiences
• Demonstrated capability in extracting necessary information from meetings and written communications
• Understanding of how to navigate conflicting priorities across different teams within the company