GenAI Data Engineer
Tiger Analytics Inc. Open · verified Oct 22, 2026 At a glance
Mid-level AI Engineering role at Tiger Analytics Inc. Remote, United States · full-time · no salary stated · we estimate $132,450–$205,151 across the United States.
Tiger Analytics Inc. has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build pipelines that ingest, process and store large volumes of unstructured data in Snowflake and GCP
- Use Snowflake Directory Tables, Scoped URLs and Snowpark to make unstructured data usable for queries
- Connect GCP and Snowflake through cloud-based ETL/ELT workflows using BigQuery, Cloud Storage and Dataflow
- Add OCR, NLP entity extraction and Document AI to turn unstructured files into structured data
- Improve complex SQL and Python processing so they work efficiently at petabyte scale
What you bring
- You have Dataiku expertise for data engineering work
- You can build and maintain data pipelines, integrations and infrastructure
- You can work with Snowflake and GCP, including their unstructured-data capabilities
Who this fits
This mid-level, full-time remote role in Hartford suits a data engineer comfortable working with unstructured data and AI processing tools. You’ll collaborate with data scientists, analysts and other stakeholders, with substantial individual responsibility.
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 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.