What are the responsibilities and job description for the Lead Data Engineer- Snowflake position at Tiger Analytics?
Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges. We are on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow. Our diverse team of over 6,000 technologists and consultants operates across five continents, building cutting-edge ML and data solutions at scale. Join us to do great work and shape the future of enterprise AI.
We are seeking an experienced Lead Data Engineer with expertise in AWS & Snowflake to join our data team. As a Lead Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, data integration processes, and data infrastructure using Cloud Snowflake DBT. You will collaborate closely with data scientists, analysts, and other stakeholders to ensure efficient data flow and support data-driven decision making across the organization.
Requirements
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
We are seeking an experienced Lead Data Engineer with expertise in AWS & Snowflake to join our data team. As a Lead Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, data integration processes, and data infrastructure using Cloud Snowflake DBT. You will collaborate closely with data scientists, analysts, and other stakeholders to ensure efficient data flow and support data-driven decision making across the organization.
Requirements
- 10 years of overall industry experience specifically in data engineering
- 8 years of experience building and deploying large-scale data processing pipelines in a production environment
- Strong proficiency in Python, SQL, and PySpark
- Expert-level AWS (S3, Glue, Lambda) and Databricks/Apache Spark for batch and real-time streaming
- Deep expertise in the Snowflake Cloud Data Platform, including datamart development and SnowPro-level optimization
- Lead the implementation of dbt (Core/Cloud) and Matillion for robust ETL/ELT workflows
- Leverage AWS best practices to ensure pipelines are cost-effective, reliable, and high-performing
- Develop and maintain version-controlled data workflows using Git and automated deployment pipelines
- Understanding of Datawarehouse (DWH) systems, and migration from DWH to data lakes/Snowflake
- Strong problem-solving skills and the ability to handle complex data challenges
- Build processes supporting data transformation, data structures, metadata, dependency and workload management
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.