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