Data Engineer-SnowPro - DBT

Role Overview: As a Senior Data Engineer, your role will involve establishing a clear vision for data engineering practices and harmoniously aligning it with the data architecture. Collaboration with product managers is essential to comprehend business requirements and identify opportunities for data leverage. You will be responsible for creating, designing, and developing complex data processing pipelines. A cooperative relationship with the data intelligence team is necessary for designing scalable implementations and production of data models. Additionally, you will be writing clean, iterative code and utilizing various continuous delivery practices to deploy, support, and operate data pipelines. Your role will also involve selecting suitable data modeling techniques, optimizing and designing physical data models, and understanding the trade-offs between various data modeling techniques. Key Responsibilities: - Establish a clear vision for data engineering practices and align it with the data architecture - Collaborate with product managers to understand business requirements and identify opportunities for data leverage - Create, design, and develop complex data processing pipelines - Work closely with the data intelligence team to design scalable implementations and produce data models - Write clean, iterative code and utilize continuous delivery practices for deploying, supporting, and operating data pipelines - Select suitable data modeling techniques, optimize and design physical data models, and understand trade-offs between different techniques Qualifications Required: - Passion for data with the ability to build and operate data pipelines and maintain data storage within distributed systems - Deep understanding of data modeling and experience with modern data engineering tools and platforms, including cloud warehousing tools - Ability to go deep into coding and lead junior members to implement solutions - Experience in defining and implementing data governance and security policies - Knowledge of DevOps and familiarity with all phases of the data & release life cycle - Familiarity with AWS and Azure Cloud - Extensive knowledge of Snowflake, SnowPro Core certification is a must-have - Experience using DBT in at least one project to deploy models in production - Configuration and deployment of Airflow, integration of various operators in airflow (especially DBT & Snowflake) - Designing build, release pipelines, and understanding the Azure DevOps Ecosystem - Excellent understanding of Python (especially PySpark) and ability to write metadata-driven programs - Familiarity with Data Vault (Raw, Business) and concepts like Point In Time, Semantic Layer - Resilience in ambiguous situations and the ability to articulate problems in a business-friendly way - Belief in documenting processes, managing artifacts, and evolving them over time Good to have skills: - Experience with data visualization techniques and ability to communicate insights based on the audience - Experience with Terraform and Hashicorp Vault highly desirable - Knowledge of Docker and Streamlit is a big plus. Role Overview: As a Senior Data Engineer, your role will involve establishing a clear vision for data engineering practices and harmoniously aligning it with the data architecture. Collaboration with product managers is essential to comprehend business requirements and identify opportunities for data leverage. You will be responsible for creating, designing, and developing complex data processing pipelines. A cooperative relationship with the data intelligence team is necessary for designing scalable implementations and production of data models. Additionally, you will be writing clean, iterative code and utilizing various continuous delivery practices to deploy, support, and operate data pipelines. Your role will also involve selecting suitable data modeling techniques, optimizing and designing physical data models, and understanding the trade-offs between various data modeling techniques. Key Responsibilities: - Establish a clear vision for data engineering practices and align it with the data architecture - Collaborate with product managers to understand business requirements and identify opportunities for data leverage - Create, design, and develop complex data processing pipelines - Work closely with the data intelligence team to design scalable implementations and produce data models - Write clean, iterative code and utilize continuous delivery practices for deploying, supporting, and operating data pipelines - Select suitable data modeling techniques, optimize and design physical data models, and understand trade-offs between different techniques Qualifications Required: - Passion for data with the ability to build and operate data pipelines and maintain data storage within distributed systems - Deep understanding of data modeling and experience with modern data engineering tools and platforms, including cloud warehousing