IT - Workforce - Data Quality Engineer

V R Della Infotech•Montgomery, AL

2d•Onsite

About The Position

The Data Quality Engineer will improve data integrity and readiness for analytics and AI applications in an environment with low or no data maturity. The role combines data analysis and engineering, with a focus on SQL, data profiling, data pipelines, data modeling, and cloud data environments. The position involves analyzing datasets for anomalies, duplicates, outliers, and missing values; building data validation and cleansing processes; and defining measures for completeness, accuracy, timeliness, and consistency. The engineer will investigate the root causes of data issues and implement fixes, while collaborating with business stakeholders, engineering teams, and data scientists to ensure dependable data for analytics and machine learning. This is a long-term, one-year renewable contract expected to end September 30, 2026, with an extension possibility and eventual conversion to merit employment. The role is 100% onsite in Montgomery, Alabama; remote work is not allowed. The target start date is June 15, 2026. The role does not offer sponsorship.

Requirements

Must be able to navigate an environment with low or no data maturity.
Strong SQL proficiency, including complex queries for validation, transformation, and reporting.
Experience with data profiling, data cleansing, and data validation.
Experience with ETL/ELT processes and data pipelines, including SSIS.
Python skills for automation, data validation, or integration with analytics pipelines.
Understanding of data modeling and data warehouse, data lake, or lakehouse architectures.
Experience with cloud platforms such as AWS, GCP, or Azure and modern data warehouses such as Snowflake or BigQuery.
Experience with or knowledge of technologies such as Spark, Kafka/Kinesis, Hadoop, or S3.
Ability to define data quality metrics and conduct root cause analysis.
Strong problem-solving skills and attention to detail.
Ability to communicate and collaborate with business, engineering, analytics, and data science stakeholders.
Ability to document quality issues, processes, and improvements.
Must be eligible for conversion to merit employment.
Must be able to work 100% onsite in Montgomery, Alabama; remote work is not allowed.
The role does not offer sponsorship.

Nice To Haves

Experience with data profiling tools such as Microsoft Purview.
Experience with data quality observability platforms.
Experience with Jira, Snowflake, or other data governance platforms.
Experience supporting advanced analytics and AI applications.

Responsibilities

Profile data to identify anomalies, duplicates, outliers, and missing values, and apply cleansing techniques to improve data integrity.
Write complex SQL queries to validate data accuracy, transform data, and generate reports.
Support ETL/ELT data pipelines, including SSIS.
Use automation and validation scripts to improve data quality and integrate with analytics pipelines.
Apply data modeling principles and work with data warehouse, data lake, and lakehouse architectures.
Design and deploy automated data testing at scale and use observability platforms for real-time monitoring.
Define and enforce data quality standards and benchmarks, measuring completeness, accuracy, timeliness, and consistency.
Investigate root causes of data issues, such as ETL bugs, user input errors, and system failures, and implement fixes.
Collaborate with data science and machine learning teams to ensure training data is clean and reliable.
Interpret patterns in large datasets to inform data quality improvements.
Gather requirements from business, engineering, and analytics stakeholders and advocate for data quality across the organization.
Document quality issues, processes, and improvements for transparency and compliance.