A consulting firm in New York is seeking an experienced Analytics Engineer to transform raw data into reliable datasets and maintain data models and pipelines using SQL and tools like Snowflake and dbt. Ideal candidates will be proficient in data modeling, capable of collaborating with stakeholders, and experienced in implementing testing frameworks to ensure data reliability. The position offers a challenging environment where data best practices will be standardized.
Qualifications
Proficiency in SQL and data modeling.
Experience in data pipeline orchestration and data warehousing.
Ability to communicate technical concepts to diverse audiences.
Responsibilities
Transform raw data into reliable data sets.
Build and maintain data models and pipelines using SQL and dbt.
Implement automated testing frameworks for data accuracy.
Skills
SQL
Data modeling
Data pipeline orchestration
Data warehousing
Tableau
Power BI
CI/CD
Version control
Automated testing
Tools
Snowflake
dbt
Job description
Overview
Our client is looking for an experienced Analytics Engineer.
Responsibilities
Transform raw data into reliable data sets
Build and maintain data models and pipelines, often using tools like Snowflake and dbt.
Collaborate with business stakeholders to understand requirements and deliver well-defined, tested, and documented data sets that enable self-service analytics, fostering trust and consistency across the organization.
Design, develop, and maintain data models and pipelines (often using SQL and tools like dbt) to transform raw data into meaningful, structured information.
Implement automated testing frameworks to ensure data accuracy, consistency, and reliability.
Create comprehensive documentation for data models, pipelines, and processes to support self-service and ensure understanding across the organization.
Work with data analysts, data scientists, and business stakeholders to gather requirements and align data efforts with strategic business initiatives.
Build and maintain the data platform, including data pipelines, to ensure scalability and efficiency.
Standardize and enforce data management best practices, including version control, code reviews, and automated processes.
Key Skills
Proficiency in SQL, data modeling, data pipeline orchestration, and data warehousing.
Deep understanding of business requirements and use cases to ensure data meets business needs.
Ability to effectively communicate technical concepts and data insights to both technical and non-technical audiences.
Familiarity with software development best practices like CI/CD, version control, and testing.
Expertise in tools like Tableau or Power BI for creating reports and dashboards that present data findings clearly.
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