Data Engineer

Job Description: As a Data Engineer in this role, you will collaborate with client stakeholders to analyze and synthesize client data to meet business objectives, reporting dashboards, and descriptive/predictive/prescriptive analytic requirements. You will leverage best practices and industry-leading tools to profile data, develop efficient ingestion, and build semantic data layers. Additionally, you will design data models and solutions for analytical and reporting use cases. Your responsibilities will also include building and maintaining scalable data transformation workflows in dbt and Snowflake, ensuring clean, consistent, and well-modeled data sets that serve as the foundation for analytics and reporting. You will implement data quality testing, documentation, and version control within dbt to enforce best practices in data governance and maintain transparency across the analytics lifecycle. Furthermore, you will develop efficient, reusable data pipelines and Tableau use case layers that enable cross-functional teams to perform self-service analytics and advanced data exploration with minimal engineering dependency. Key Responsibilities: - Design and implement data pipelines - Optimize data processing and storage - Ensure data solutions meet performance standards - Provide technical support - Collaborate with stakeholders Qualifications: - Masters or Bachelor's degree in Data Science, Computer Engineering, Math, Statistics, Economics, or related analytics field from top-tier universities with a strong record of achievement - 3-5 years of experience with solid data engineering skills - Hands-on knowledge of traditional relational data warehouse technologies, such as SQL (including Analytical SQL functions), dbt, Tableau, Python/Pyspark - Experience in data architecture and data modeling, including creating Semantic Layer Data Models - Preferred expertise in the Sports industry - Experience in Machine Learning or NLP, such as Scikit-Learn, SpaCy, PyTorch, or Spark NLP is desirable - Prior experience in management consulting and/or analytics-based consulting is desirable Job Description: As a Data Engineer in this role, you will collaborate with client stakeholders to analyze and synthesize client data to meet business objectives, reporting dashboards, and descriptive/predictive/prescriptive analytic requirements. You will leverage best practices and industry-leading tools to profile data, develop efficient ingestion, and build semantic data layers. Additionally, you will design data models and solutions for analytical and reporting use cases. Your responsibilities will also include building and maintaining scalable data transformation workflows in dbt and Snowflake, ensuring clean, consistent, and well-modeled data sets that serve as the foundation for analytics and reporting. You will implement data quality testing, documentation, and version control within dbt to enforce best practices in data governance and maintain transparency across the analytics lifecycle. Furthermore, you will develop efficient, reusable data pipelines and Tableau use case layers that enable cross-functional teams to perform self-service analytics and advanced data exploration with minimal engineering dependency. Key Responsibilities: - Design and implement data pipelines - Optimize data processing and storage - Ensure data solutions meet performance standards - Provide technical support - Collaborate with stakeholders Qualifications: - Masters or Bachelor's degree in Data Science, Computer Engineering, Math, Statistics, Economics, or related analytics field from top-tier universities with a strong record of achievement - 3-5 years of experience with solid data engineering skills - Hands-on knowledge of traditional relational data warehouse technologies, such as SQL (including Analytical SQL functions), dbt, Tableau, Python/Pyspark - Experience in data architecture and data modeling, including creating Semantic Layer Data Models - Preferred expertise in the Sports industry - Experience in Machine Learning or NLP, such as Scikit-Learn, SpaCy, PyTorch, or Spark NLP is desirable - Prior experience in management consulting and/or analytics-based consulting is desirable