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Consultis, a premier Technical Solutions Provider and IT Staffing Firm with the single focus of pairing the right candidate with the right employment opportunity is currently searching for a Data Scientist (Onsite) for a Fulltime Direct Hire (FTE) opportunity with our client.
As a Data Scientist, you will play a critical role in managing and optimizing our client’s data warehouse, mentoring other business intelligence employees, and serving as a thought leader on data infrastructure and tools. You will collaborate closely with cross-functional teams to ensure data accuracy, develop efficient data querying methods and best in class processes, and prepare data for business analysts’ dashboarding and analysis.
My client is seeking a Data Scientist to join their Engineering/BI team and take ownership of their data infrastructure, ensuring its accuracy and efficiency, and providing valuable insights to drive data-informed decision-making.
Key Responsibilities:
Data Ownership and Management:
- Take ownership of the data through the data warehouse.
- Ensure data accuracy and quality, implementing necessary checks and validations.
- Connect and integrate third-party data sources into the data pipeline.
Tool Selection and Recommendations:
- Assess company needs and recommend data tools and technologies.
- Stay updated with industry best practices and emerging tools.
- Explore and suggest innovative solutions to improve data infrastructure
ETL and ELT Expertise:
- Have a deep understanding of both ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes.
- Develop and maintain ETL/ELT pipelines to transform raw data into usable formats.
Mentorship and Thought Leadership:
- Mentor other data scientists and business intelligence employees.
- Provide thought leadership on data infrastructure, querying, analysis and best practices.
Efficient Data Querying:
- Create proficient and efficient methods for data querying.
- Optimize data retrieval and processing to minimize latency.
Hands-On Approach:
- Be hands-on with data, infrastructure, and analysis, actively participating in data-related tasks.
Data Preparation for Analysis:
- Prepare data in a manner that enables business analysts to create dashboards and conduct meaningful analysis.
- Collaborate with analysts to understand their requirements.