Data Quality Engineer

Gravity It
Hollywood, FL, United States
4 days ago
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Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Agile Methodology Data Analysis Automation of Tests Microsoft Azure Information Systems Computer Programming Continuous Integration Information Engineering Data Governance Extract Transform Load (ETL) Data Profiling Data Warehousing
+21 more
Database Testing DevOps Python (Programming Language) Meta-Data Management Oracle (Applications) Power BI Cloud Services Standard Sql SQL Databases Tableau (Software) Azure Data Factory Snowflake Apache Spark Git Data Lakes Pyspark Information Technology Data Lineage Data Management Data Pipelines Databricks

Job description

We are seeking a Data Quality Engineer to design, build, and support enterprise data quality frameworks, monitoring solutions, and automated validation processes. This role partners with Data Engineering, Governance, Analytics, and Business teams to ensure trusted, reliable, and high-quality data across the organization., * Data Quality Design and implement enterprise data quality frameworks and controls.

  • Develop automated validation, monitoring, and exception reporting solutions.
  • Measure and improve data quality across Accuracy, Completeness, Consistency, Validity, Integrity, Uniqueness, and Timeliness.
  • Partner with Data Governance teams to operationalize data quality standards.
  • Investigate and resolve complex data quality issues through root cause analysis.
  • Data Engineering Build and optimize ETL/ELT pipelines using Databricks, Spark, Python, SQL, and Azure Data Factory.
  • Embed data quality validations into ingestion and transformation processes.
  • Develop reusable validation components and automated testing frameworks.
  • Support cloud data platforms and modernization initiatives.
  • DevOps & Collaboration Build and maintain CI/CD pipelines and Git-based deployment processes.
  • Collaborate with engineers, architects, analysts, and business stakeholders.
  • Translate business requirements into scalable technical solutions.
  • Present findings and recommendations to technical and business audiences.

Requirements

  • Required Qualifications Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field.
  • 5+ years of experience in Data Engineering, Data Quality Engineering, or related roles.
  • Strong expertise in:
  • SQL
  • Python
  • Databricks & Spark
  • Azure Data Factory (ADF)
  • Oracle and modern cloud data platforms
  • Git and CI/CD pipelines
  • Strong analytical, troubleshooting, and root cause analysis skills.
  • Excellent communication and stakeholder management abilities.
  • Preferred Qualifications Experience with Ataccama Data Quality Platform.
  • Knowledge of Data Governance, MDM, data lineage, and metadata management.
  • Experience with Delta Lake, Azure cloud services, Snowflake, Power BI, or Tableau.
  • Experience implementing automated data testing and observability solutions.
  • Experience working in Agile environments.

Technical Skills

Data Quality: Experience with Ataccama or other equivalent Data Quality (DQ) tools.

, Data Profiling, Monitoring, Validation, Governance, Data Lineage

Data Engineering: Databricks, ADF, Spark, Delta Lake, ETL/ELT, Data Warehousing

Programming: SQL, Python, PySpark

DevOps: Git, Azure DevOps, CI/CD, Automated Testing, The ideal candidate has previously built or supported a Data Quality platform, preferably using Ataccama, and has hands-on experience developing enterprise-grade data engineering solutions using Databricks, Python, SQL, ADF, Git, and CI/CD practices. They are equally comfortable discussing architecture with engineers, presenting findings to leadership, and diving deep into data to identify and resolve quality issues. xrbllit They bring a passion for delivering trusted, high-quality data that drives business decisions.

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