Data Quality Engineer

Ampcus, Inc; Milwaukee (WI); On-site; USD 85,000 - 120,000; Full time

Job summary

Ampcus Inc. is seeking a Data Quality Engineer to join our Milwaukee team. You will profile data, implement automated validation within ETL pipelines, and build real-time monitoring for data quality.

You will work with engineering to resolve discrepancies and ensure governance and regulatory compliance across data handling. The role requires strong SQL and Python skills, experience with dbt, Great Expectations, and data quality tools, plus experience with Snowflake, AWS, Azure or Databricks.

Qualifications

• Experience analyzing data sources to understand structure, quality, and content.
• Experience designing and implementing automated data validation in ETL pipelines.
• Ability to build reusable data quality rules and monitoring systems.

Responsibilities

• Analyze data sources to profile structure, content, and quality; identify anomalies and missing values.
• Design and implement automated data validation frameworks within ETL pipelines.
• Build reusable data quality rules and monitoring systems for real-time detection of issues.
• Investigate data discrepancies and work with engineering teams for permanent resolutions.
• Bridge business requirements with technical implementation for good data outcomes.
• Ensure data handling meets regulatory standards like GDPR or HIPAA, including masking and lineage.

Skills

Data profiling

Automated testing

Framework development

Root cause analysis

Stakeholder liaison

Governance & compliance

Education

Bachelor's degree in Computer Science or related field

Tools

dbt

Great Expectations

Soda

Monte Carlo

Informatica Data Quality

Databricks

Snowflake

Power BI

Tableau

SQL

Python

Spark

Hadoop

Kafka

Airflow

AWS

Redshift

S3

Azure

Job description

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team. Job Title: Data Quality Engineer. Location: Milwaukee, WI.

Key Responsibilities:

• Data Profiling & Assessment: Analyzing data sources to understand structure, content, and quality; identifying anomalies, duplicates, or missing values.
• Automated Testing: Designing and implementing automated data validation frameworks (e.g., dbt tests, Great Expectations) within ETL pipelines.
• Framework Development: Building reusable data quality rules and monitoring systems to detect issues in real-time.
• Root Cause Analysis: Investigating why data discrepancies occur and working with engineering teams to drive permanent resolutions.
• Stakeholder Liaison: Bridging the gap between business requirements (what "good data" looks like for a product) and technical implementation.
• Governance & Compliance: Ensuring data handling meets regulatory standards like GDPR or HIPAA, including implementing data masking and lineage.

Required Technical Skills:

• Languages: Expert-level SQL for complex querying and Python for automation scripting.
• Data Quality Tools: Proficiency in frameworks like dbt, Great Expectations, Soda, Monte Carlo, or Informatica Data Quality, Databricks, Snowflakes.
• Data Visualization: Proficiency in Power BI, Tableau.
• Cloud Platforms: Hands-on experience with modern data stacks like Snowflake, AWS (Redshift/S3), Azure, or Databricks.
• Big Data Tech: Knowledge of Spark, Hadoop, Kafka, or Airflow for managing and monitoring large-scale pipelines.

Preferred Qualifications:

• Experience: Typically, 3-8 years in Data Engineering, ETL Testing, or a specialized Data Quality role.
• Education: A degree in Computer Science, Data Science, or a related technical field.
• Soft Skills: High attention to detail, strong communication for explaining technical issues to non-technical stakeholders, and critical thinking for spotting hidden patterns.

Ampcus is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veterans or individuals with disabilities.