Intermediate Business Intelligence Data Analyst
1 month ago
We are a data-driven company that helps our clients make informed decisions by providing them with actionable insights from our rich data collection. We are looking for a skilled data engineer to join our team and help us drive value from our data.
About the RoleThe ideal candidate will have a strong analytical and mathematical background, with experience in building and maintaining data pipelines, data visualization, and data exploration. They will be responsible for working closely with our development team, data analysts, and BI analysts to build and maintain data flows that support our reporting requirements.
Key Responsibilities- Design and implement data pipelines that clean, transform, and aggregate data from disparate sources
- Develop models that can be used to make predictions and answer questions for the overall business
- Work closely with our development team to make iterative improvements to our back-end systems, particularly our reporting DB
- Model front-end and back-end data sources to help draw a more comprehensive picture of user flows throughout the system
- Build data pipelines that deliver quality usable data to data analysts and BI analysts for reporting
- Gather and extract data from the database for analysis
- Clean and prepare data for analysis
- Quality control our data processes and tables
- Identify, analyze, and interpret market data for clients
- Produce accurate BI reports and dashboards within agreed-upon timeframes
- Respond to data-related requests and queries and keep track of all requests
- Collaborate with key stakeholders on all aspects of report creation, including deadlines, deliverables, edits, and recommendations
- Present information and communicate findings generated from data to stakeholders
- Bachelor's degree in computer science, information technology, engineering, or related analytical discipline
- Three or more years of experience with Python, SQL, and data visualization/exploration tools
- Familiarity with common Python-based ETL tools such as PySpark or Apache Airflow
- Familiarity with Kimball and Inmon data warehousing approaches
- Familiarity with the AWS ecosystem, specifically Redshift, RDS, and EC2
- Communication skills, especially for explaining technical concepts to non-technical business leaders
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