Data Engineer - Snowflake
At a glance
Mid-level Data Engineering role at Tiger Analytics Inc. Remote, Canada · full-time · no salary stated · we estimate CA$90,000–CA$121,500.
Tiger Analytics Inc. has not published a salary for this role. The figure below is our estimate, not theirs.
remoteroles summary, based on the employer's posting.
What you'll do
- Design and put advanced analytics capabilities into operation, including complex data-processing and transformation pipelines
- Build and run large-scale data pipelines in production, using Python to shape and optimize data flows
- Create processes for data structures, metadata, dependencies and workload management
- Work with database systems, data models and unstructured datasets to support analytics and business insights
What you bring
- At least twelve years in data engineering, with substantial work across AWS and AI
- At least eight years building and deploying large data pipelines in production settings
- Advanced Python, SQL and PySpark skills, plus deep experience with Snowflake or Databricks on AWS and dbt
- Working knowledge of relational databases, data warehouse migration, ETL and ELT patterns, and data modeling
Who this fits
This role suits a senior data engineer comfortable with complex datasets, production pipelines and analytics work. The posting describes a remote, full-time position in Toronto and emphasizes individual responsibility and collaboration with cross-functional teams.
From the employer
Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world.
The Data Engineer will be responsible for architecting, designing, and implementing advanced analytics capabilities. The right candidate will have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards, be comfortable using visualization tools, and be able to apply your skills to generate insights that help solve business challenges. We are looking for someone who can bring their vision to the table and implement positive change in taking the company's data analytics to the next level.
Requirements
- 12+ years of overall industry experience specifically in data engineering with a heavy focus on the AWS Cloud stack and AI.
- 8+ years of experience building and deploying large-scale data processing pipelines in a production environment.
- Advanced proficiency in Python, SQL, and PySpark.
- Creating and optimizing complex data processing and data transformation pipelines using python
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
- Deep experience with Snowflake/Databricks on AWS, dbt, and distributed computing frameworks like Apache Spark.
- Understanding of Datawarehouse (DWH) systems, and migration from DWH to data lakes/Snowflake
- Understanding of ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models
- Strong analytic skills related to working with unstructured datasets
- Build processes supporting data transformation, data structures, metadata, dependency and workload management
- Experience supporting and working with cross-functional teams in a dynamic environment
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, 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.