GenAI Data Engineer

Tiger Analytics; Hartford (CT); On-site; USD 90,000 - 120,000; Full time

Job summary

A leading analytics consulting firm is seeking an experienced Data Engineer with expertise in Dataiku. In this role, you will be responsible for designing and maintaining data pipelines and integrating AI tools for data transformation. The ideal candidate should have strong skills in SQL, Python, and cloud technologies like GCP and Snowflake. This position offers significant career development opportunities in a collaborative and entrepreneurial environment.

Qualifications

• Experience in designing and implementing data pipelines.
• Proficient in SQL and Python for large-scale data environments.
• Familiarity with cloud platforms such as GCP.

Responsibilities

• Design and implement robust data pipelines for unstructured data.
• Integrate AI tools into data engineering workflows.
• Tune SQL queries and Python jobs for performance.

Skills

Data Engineering

Dataiku

SQL

Python

Cloud Infrastructure

AI Integration

Tools

Snowflake

GCP

BigQuery

Cloud Storage

Dataflow

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 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.

• 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.

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.