Data QA Engineer

Responsibilities

Take ownership of end to end data quality

Understand and Contribute to the event model design

Build and automate testing frameworks around data ingestion pipelines.

Write complex SQL queries on tables with hundreds of millions of records and ensure data integrity is maintained throughout the ETL lifecycle.

Design test cases and write python/SQL scripts to validate data integrity and identify gaps and opportunities in our pipelines.

Track data issues and work with team leads from discovery to resolution.

Collaborate with the analytic teams to conduct data quality investigations, improve automation and tools.

Review current tools and enhance them to help with data integrity.

Minimum Qualifications

5+ years of work experience in QA, preferably in data or relevant space

Demonstrable knowledge, experience, skill, and proficiency with the following:

Scrum/Agile methodologies

SDLC

Python (at least reading)

SQL

Experience with different facets of QA tests such as functional progression & regression, integration, performance, load, UAT, and operational readiness testing

Must be self-motivated, able to work independently, and thrive in a fast-paced, multi-tasking, high productivity environment while maintaining excellent working relationships with people in a wide variety of functional areas

Excellent verbal and written communication skills

Preferred Qualifications

Applied experience with Databricks and/or Azure ML

Strong coding abilities in one or more scripting languages like Python or SQL

Understanding of compliance, security, and risk domains along with associated patterns and data elements

Use of one of the following vendor reporting solutions: PowerBI or Tableau

Understanding of product and services activation, use, and transaction models and data

Understanding of statistical analysis and machine learning tools and practices

Understanding of Cloud-centric data processing and visualization approaches including SQL and NoSQL databases with exposure to Azure SQL, Azure Cosmos DB, Data Factory, Synapse, Azure Data Lake, etc

Familiarity with Agile software delivery including application lifecycle mgmt (Jira/Azure DevOps/VSTS, Git).

All your information will be kept confidential according to EEO guidelines.

Ex Parte provides our customers with the data and insight to make smart and informed decisions on the most important legal issues facing their organizations.

We are is looking for talented, enthusiastic senior data engineers who share our passion for big data, AI, and machine learning and are excited by seemingly-impossible challenges. As an early employee, you must be amazingly entrepreneurial and thrive in a fast-paced environment where the solutions aren’t predefined.

Every year, corporations spend more than $250B on litigation in the United States alone. And yet, critical decisions such as whether to litigate or settle, or where to file suit or which attorney to hire, are all made the same way they were 100 years ago.

We are applying artificial intelligence, machine learning, and natural language processing to provide our customers with the insight they need to make highly informed decisions and gain a winning advantage. Think of it like Moneyball, but for a market more than 20x the size of Major League Baseball.

Originally posted on Himalayas