Description:
We are hiring an Analytics Engineer plays a crucial role at the intersection of Data Engineering, Data Science, and Business Intelligence, producing and maintaining descriptive analytics solutions that drive value to the business.
Supporting Meaningful Work
- Work collaboratively with business partners and cross-functional teams to understand business context and needs and deliver on analytics requirements to solve problems. This involves collecting, cleaning, and harmonizing data to create and maintain analytics-ready datasets and analyzing data to create compelling visualizations.
The output of the Analytics Engineer recommends problem-solving action and enables strategic decision-making in the business.
Who You Are
- Strong analytical and problem-solving skills with the ability to interpret complex datasets and provide insights for action
- Strong communication and storytelling skills, ability to communicate about data insights with a diverse audience
- Ability to collaborate on multi-disciplinary Agile teams to deliver analytics solutions
- Experience in understanding business stakeholders’ processes and problems and translating into data and analytics solutions
- Ability to consult and collaborate with business stakeholders to enable self-service analytics using data in the Lakehouse
Minimum Qualifications
- Bachelor’s degree required; advanced degree in Statistics, Data Science, Information Systems, Business Analytics or related fields is preferred
- 2+ years of prior independent, academic, internship, or work-related experience
- Knowledge of statistics including distributions, outliers, normalization, and trends for responsible data analysis
- Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn, Plotly, Streamlit) to create compelling visual analytics
- Familiarity with cloud data platforms such as Databricks or Snowflake for deploying analytics solutions
- Proficiency in programming languages such as Python, R, or SQL for data manipulation and analysis
- Proficiency in working with structured and unstructured data
- Experience in data modeling and designing efficient ETL processes, with a particular focus on implementing Medallion Architecture within a Data Lakehouse environment
- Experience in producing analytics-ready datasets through cleaning, transformation, and harmonization
- Understanding of data quality, governance, and security best practices