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Sr data quality engineer

Sydney
PeopleLogic
Quality Engineer
Posted: 4 February
Offer description

Job Description – Senior Data Quality Engineer

Location:
Sydney, Australia

Contract Duration:
6 Months

Experience:
7–10 Years

Role Overview

We are seeking an experienced
Senior Data Quality Engineer
to ensure the accuracy, consistency, and reliability of enterprise data platforms. The role involves close collaboration with data engineering and analytics teams to design and maintain automated data quality frameworks across ETL pipelines and cloud data warehouses.

Key Responsibilities

* Design, develop, and maintain
automated data quality and validation frameworks
* Collaborate with data engineering teams to understand
ETL processes
and identify data quality risks
* Perform
data profiling, cleansing, and validation
using
Alteryx
,
SQL
, and
Python
* Build, optimize, and execute data quality checks in
Snowflake
* Monitor data quality metrics and prepare reports highlighting issues and trends
* Work with stakeholders to define and enforce
data quality rules, standards, and governance
* Troubleshoot and resolve data quality issues within defined SLAs
* Document data quality processes, standards, and best practices
* Mentor junior team members and contribute to continuous improvement initiatives

Required Skills & Qualifications

* Bachelor's or Master's degree in Computer Science, IT, or related field
* 7–10 years of experience as a
Data Quality Engineer, Data Analyst, or similar role
* Strong hands-on experience with
ETL processes and tools
* Expertise in
Snowflake Data Warehouse
* Hands-on experience with
Alteryx
for data preparation and automation
* Strong
SQL
skills for complex queries and data validation
* Proficiency in
Python
for scripting, automation, and testing
* Good understanding of
data quality and data governance frameworks
* Excellent analytical, problem-solving, and communication skills
* Ability to work independently and collaboratively in a fast-paced environment

Preferred / Nice to Have

* Experience with other data quality tools or frameworks
* Cloud exposure (
AWS / Azure
)
* Knowledge of
Data Vault architecture
* Experience with
dbt

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