Data Engineer – AI Software Platform

JR Associates Group LLC; United States; Remote; USD 80,000 - 120,000; Full time

Job summary

A leading company is seeking a Data Engineer to enhance their intelligence platform using AI for legal case analysis. The role involves managing the entire analytic life cycle, including data retrieval, wrangling, and visualization, utilizing tools like Airflow and Python. Ideal candidates will have experience in data modeling and reporting using PostgreSQL and Redshift, contributing to both internal operations and client-facing products.

Qualifications

• Experience with ETL processes and data orchestration using Airflow.
• Proficient in writing queries in PostgreSQL and Redshift.
• Ability to create data models and dashboards for internal and client-facing reports.

Responsibilities

• Orchestrate and manage ETL processes using Airflow and Python.
• Write data models and queries for reporting and analytics.
• Build internal and client-facing dashboards and reports.

Skills

ETL processes

Data visualization

Data modeling

PostgreSQL

Redshift

Python

Airflow

Tools

LookML

PowerBI

Tableau

Qlik

Job description

We are working a search for our client that is building an intelligence platform that uses AI to accelerate & improve the accuracy of discovering & evaluating legal cases. They have created one of the world’s largest repositories of health records for individuals in legal liability cases.

They transform terabytes of unstructured data into real-time, indexed medical and legal knowledge bases. Theirdocument processing pipeline is the industry’s fastest & uses Scala on AWS.

Seeking a Data Engineer to be responsible for functions across the entire analytic life cycle, from retrieval, wrangling, aggregation, visualization, and optimization. You’ll operate heavily within their data warehouse, writing queries against large volumes of structured and unstructured information. You’ll synthesize this information into cohesive and clear reports to be used both internally within the organization, but also as embedded products within the platform.

Responsibilities:

1. Use Airflow and Python to orchestrate and manage ETL processes
2. Write data models within LookML (experience in PowerBI, Tableau, or Qlik is fine)
3. Write queries in PostgreSQL and Redshift
4. Build internal reports and dashboards that guide Pattern’s internal operations and decisions
5. Build embedded, client-facing reports and dashboards that are deployed as a part of the Pattern platform
6. Build tools to monitor the health and responsiveness of Pattern’s analytic products