Mars United Commerce is looking for an Analytics Engineer to develop and maintain the data infrastructure that supports their analytics engineering capabilities, ensuring data quality and accessibility for data scientists and analysts, and implementing best practices for data governance and security.
Requirements
- Proficiency in SQL for data querying and manipulation.
- Experience with data warehousing solutions.
- Design, implement, and manage ETL workflows to ensure data is accurately and efficiently collected, transformed, and loaded into our data warehouse.
- Proficiency in programming languages such as Python and R.
- Experience with cloud platforms such as AWS, Azure, and Google Cloud.
- Experience in developing and deploying machine learning models.
- Knowledge of machine learning engineering practices, including model versioning, deployment, and monitoring.
Responsibilities
- Develop and maintain data pipelines and ETL processes.
- Optimize data infrastructure for efficient data processing.
- Ensure data quality and accessibility for data scientists and analysts.
- Implement data governance and security best practices.
- Develop and optimize machine learning models by processing, analyzing and extracting data from varying internal and external data sources.
- Develop supervised, unsupervised, and semi-supervised machine learning models using state-of-the-art techniques to solve client problems.
- Establish and create scalable and intuitive reporting methodologies through Power BI, suggesting the best representation and visualizations.
Other
- 3-5 years of industry experience in a data analytics or related role.
- Collaborate with cross-functional teams to address data needs and challenges.
- Support annual planning initiatives with clients.
- Work closely with cross-functional teams, including analysts, product managers and domain experts to understand business requirements, formulate problem statements, and deliver relevant data science solutions.
- Show up - be accountable, take responsibility, and get back up when you are down.
