Toronto, Ontario, Canada
Open 6 months, first seen by us 185 days agoWork setup in the employer’s posting: RemoteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Architect, design and implement advanced analytics capabilities
Create and optimize complex data processing and transformation pipelines in Python
Build self-service dashboards and generate business insights
Build processes for data transformation, structures, metadata and workload management
Migrate data warehouses to data lakes or Snowflake
responsible for architecting, designing, and implementing advanced analytics capabilities
Creating and optimizing complex data processing and data transformation pipelines using python
experience building self-service dashboards
Build processes supporting data transformation, data structures, metadata, dependency and workload management
migration from DWH to data lakes/Snowflake
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
Deep experience with Snowflake/Databricks on AWS, dbt, and distributed computing frameworks like Apache Spark
Understanding of ELT and ETL patterns and when to use each
From the employer’s posting.
Open 6 monthsWe first saw this posting 185 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 185
Up longer than most. Similar jobs usually come down between day 6 and day 56.
Well past Tiger Analytics’s usual: its jobs come down by about day 68.
From 13,355 similar postings that came down, and 27 of Tiger Analytics’s. Coming down is not always a hire.
74 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- 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 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
- 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.
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 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
- 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
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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
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.
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Toronto, Ontario, Canada
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