Data Engineer - Snowflake

Tiger Analytics; Toronto; On-site; CAD 80,000 - 100,000; Full time

Job summary

An established industry player is seeking a talented Data Engineer to join its dynamic team. This role offers the chance to architect and implement advanced analytics capabilities, working with large and complex data sets. The ideal candidate will have extensive experience in data engineering, particularly in building and deploying data processing pipelines. You'll leverage your skills in Python, SQL, and PySpark to create impactful data transformations and insights. With significant career development opportunities, this position is perfect for those looking to thrive in a challenging and entrepreneurial environment, making a real difference in the analytics landscape.

Qualifications

• 8+ years of industry experience in data engineering with a focus on large-scale data processing.
• Strong experience in Python, SQL, and PySpark for data transformation and processing.

Responsibilities

• Architect and implement advanced analytics capabilities for large and complex data sets.
• Build and deploy data processing pipelines in a production environment.

Skills

Data Engineering

Python

SQL

PySpark

Data Transformation

Analytic Skills

Working with Unstructured Datasets

Tools

Snowflake

DBT

Job description

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 100 companies, enabling them to generate business value from data. Our business value and leadership have 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 their 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.

Responsibilities:

1. 8+ years of overall industry experience specifically in data engineering
2. 5+ years of experience building and deploying large-scale data processing pipelines in a production environment
3. Strong experience in Python, SQL, and PySpark
4. Creating and optimizing complex data processing and data transformation pipelines using Python
5. Experience with Snowflake Cloud Datawarehouse and DBT tool
6. Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
7. Understanding of Datawarehouse (DWH) systems, and migration from DWH to data lakes/Snowflake
8. Understanding of ELT and ETL patterns and when to use each, including understanding of data models and transforming data into the models
9. Strong analytic skills related to working with unstructured datasets
10. Build processes supporting data transformation, data structures, metadata, dependency, and workload management
11. Experience supporting and working with cross-functional teams in a dynamic environment

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.