Data Quality Engineer

Insperity•Houston, TX

5d•Hybrid

About The Position

This position is responsible for ensuring delivered products meet or exceed quality standards. Implements quality mechanisms such as functional, integration, performance, security, and other tests as part of the Data Engineering organization. Ensures data quality metrics and indicators are available for easy consumption by internal and external customers. Collaborates regularly with engineers, architects, analysts, data scientists, and business users across various data initiatives to ensure data quality practices remain consistent.

Requirements

Bachelor's Degree in Computer Science, a related field, or four years of related work experience in the Business Intelligence/Data Engineering field specifically, is required.
Three to five years of professional experience in information systems is required with at least one (1) years’ experience testing, developing, architecting, managing, or maintaining enterprise grade software systems, database administration, or similar discipline.
Deep understanding and practical experience with common automated data quality and observability frameworks, e.g. Great Expectations, dbt, pytest, Talend, or similar.
Deep understanding and practical experience with SQL.
Ability to automate testing and integrate within CICD pipelines, primarily using Python.
Understanding of various ‘big data’ management tools/techniques, e.g. Hadoop, Snowflake, Redshift, Tableau, PowerBI, Databricks, etc.
Strong consensus building skills and the ability to find common ground or mutual agreement across complex topics involving compromise, negotiation, and similar tactics.
Exhibits a passion for learning and continuous improvement. Takes responsibility for acquiring new skills and broadening knowledge.
Exhibits a commitment to the utilization of defined standards and processes.
Strong verbal and written communication skills, with an ability to express complex technical concepts in business terms and maintain effective work relations with those encountered in the course of employment.
Proactive at identifying and recommending areas for improvement and increased reliability.
Ability to create technical documentation and a desire to share knowledge amongst team members.
Understanding of data governance principles.

Responsibilities

Participates in the engineering of data pipelines while ensuring the quality metrics are sufficiently met.
Partners with stakeholders to ensure quality dimensions are understood and engineered into solutions.
Identifies, designs, and implements process improvements with a heavy focus on automation, data delivery optimization, self-service, and scalability.
Works seamlessly with stakeholders including Executives, Product Management, Centers of Excellence, and others.
Participates in creation and testing of large, complex data sets to meet business requirements.
Ensures data security across all implementations, data centers, cloud providers, client machines, etc.
Collaborates with team members as we build and optimize our data assets into an innovative competitive advantage.