Data Engineer

DataBuck Data Quality Engineer / Consultant

Position Title: DataBuck Data Quality Engineer Location: Remote/Hybrid Experience: 5+ Years Employment Type: Full-Time / Contract

Job Summary

We are seeking an experienced DataBuck Data Quality Engineer to design, implement, and manage enterprise data quality monitoring solutions using the DataBuck platform. The ideal candidate will have strong expertise in data quality management, data governance, database technologies, ETL processes, and cloud data platforms. The candidate will work closely with data engineering, analytics, and business teams to ensure data accuracy, completeness, consistency, and reliability across enterprise systems.

Key Responsibilities

• Implement and maintain DataBuck-based data quality frameworks and validations.
• Configure and manage automated data quality checks, profiling, anomaly detection, and monitoring.
• Develop and maintain business and technical data quality rules.
• Perform root cause analysis on data quality issues and coordinate remediation efforts.
• Integrate DataBuck with ETL/ELT pipelines, data lakes, and cloud data platforms.
• Create dashboards, alerts, reports, and data quality scorecards.
• Collaborate with Data Governance, Data Engineering, and Business teams to define quality KPIs.
• Support data reconciliation and cross-system validation processes.
• Monitor data pipelines and ensure compliance with enterprise data governance standards.
• Optimize DataBuck implementations for performance and scalability.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
• 5+ years of experience in Data Quality, Data Governance, Data Engineering, or Analytics.
• Hands-on experience with DataBuck implementation and administration.
• Strong SQL skills with experience in relational databases such as Oracle, SQL Server, PostgreSQL, or MySQL.
• Experience working with large-scale data environments and data warehouses.
• Knowledge of ETL tools such as Informatica, DataStage, Talend, SSIS, or Azure Data Factory.
• Experience with cloud platforms such as Azure, AWS, or Google Cloud.
• Understanding of data profiling, validation, reconciliation, observability, and anomaly detection concepts.
• Strong troubleshooting and analytical skills.

Preferred Qualifications

• Experience with Hadoop, Spark, Databricks, Snowflake, or BigQuery.
• Knowledge of Data Governance frameworks and Metadata Management.
• Familiarity with Python, Shell scripting, or Java.
• Experience working in Agile/Scrum environments.
• Data Management or Cloud certifications are a plus.

Technical Skills

• DataBuck Administration & Configuration
• Data Quality Monitoring & Validation
• Data Profiling & Data Reconciliation
• SQL & Database Management
• ETL/ELT Processes
• Azure Data Factory / AWS Glue / GCP Data Services
• Data Warehousing
• Data Governance & Metadata Management
• Python/Shell Scripting
• Dashboard & Reporting Tools

Nice to Have

• Experience with Monte Carlo, Great Expectations, Collibra, Informatica DQ, or similar data quality tools.
• Exposure to AI/ML-driven data quality and observability solutions.
• Experience supporting enterprise-scale data platforms.

Expected Deliverables

• Enterprise-wide data quality monitoring framework.
• Automated validation and reconciliation processes.
• Data quality scorecards and KPI reporting.
• Incident management and root cause analysis documentation.
• Data governance and compliance support.