Posting record
Open 9+ days
- Tiger Analytics' site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Tiger Analytics, so its true age is longer.
Last checked Nov 4, 2026.
How well do you match?
See how much of this posting your resume shows, and what it's missing.
Upload your resumeWhat the posting discloses
Not stated: Pay, real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Some employers add pay only on their own site. Check the original posting before you rule it out.
Skills mentioned
About the role
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 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.
We are seeking an experienced Data Engineer with expertise in Dataiku to join our data team. As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, data integration processes, and data infrastructure. 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
- Design and implement robust data pipelines that ingest, process, and store unstructured data formats at scale within Snowflake and GCP .
- Leverage Snowflake’s unstructured data capabilities (Directory Tables, Scoped URLs, Snowpark) to make "dark data" queryable and actionable.
- Build and maintain cloud-native ETL/ELT processes using BigQuery, Cloud Storage, and Dataflow, ensuring seamless integration between GCP and Snowflake.
- Instead of just using LLMs, you will integrate AI tools (OCR, NLP entities, Document AI) into the engineering flow to transform unstructured blobs into structured insights.
- Tune complex SQL queries and Python-based processing jobs to handle petabyte-scale environments efficiently.
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.
Something wrong with this posting?