Analytics Engineer

Keystone Cooperative • Indianapolis, IN

1d • Onsite

About The Position

An Analytics Engineer plays a pivotal role in transforming raw data into actionable insights that drive business decisions. This position is ideal for individuals who possess a robust blend of technical proficiency , analytical acumen, and strategic thinking. The Analytics Engineer collaborates with cross-functional teams to ensure data integrity, optimize data workflows, and facilitate data-driven decision-making. Must be authorized to work in the United States now and in the future, without company sponsorship. Must be about to work onsite in the corporate office in Indianapolis, Indiana. (This role is not hybrid or remote).

Requirements

• Proficiency in SQL, Python, and data warehousing technologies
• Experience with ETL tools such as Fivetran , Airbyte , Azure Data Factory.
• Knowledge of working with development best practices such as Version Control ( Github ) and working in a CI/CD environment
• Excellent analytical and problem-solving skills, with a keen ability to troubleshoot and resolve data-related issues.
• Effective written and verbal communication skills, with an ability to articulate complex technical concepts to non-technical stakeholders.
• Demonstrated ability to work collaboratively in a team environment, managing multiple projects and priorities simultaneously.
• Ability to adapt to changing business requirements and work in a fast-paced, dynamic environment.
• Educational Background: Bachelor’s or Master’s degree in Computer Science , Statistics , Information Systems, or related quantitative field.

Nice To Haves

• Snowflake and dbt experience a plus.

Responsibilities

• Design, develop, and maintain data pipelines using ETL (Extract, Transform, Load) processes to ensure data is efficiently and accurately integrated from disparate sources into the data warehouse.
• Architect and manage scalable data warehouse solutions to store large volumes of structured and unstructured data, ensuring data is readily accessible for analysis.
• Develop and implement data models that reflect business processes and requirements, enabling effective data analysis and reporting.
• Establish and enforce data quality standards, performing routine data validation and cleansing to maintain high data integrity.
• Optimize data processing and query performance to enhance the efficiency of data retrieval and analysis.
• Work closely with business stakeholders to understand data needs and translate them into technical requirements, ensuring alignment with business goals.
• Create comprehensive technical documentation for data pipelines, data models, and analytics solutions, promoting knowledge sharing and ensuring continuity.
• Keep abreast of emerging technologies and best practices in data engineering and analytics, recommending and implementing innovative solutions where applicable.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level