Posted:21 hours ago|
Platform:
On-site
Part Time
ROLES & RESPONSIBILITIES
Core Skills
1. Data Quality Development & Monitoring
Design and implement automated data quality rules and validation checks using Databricks (Delta Lake) and PySpark.
Build and operationalize data quality workflows in Ataccama ONE / Ataccama Studio.
Perform data profiling, anomaly detection, and reconciliation across systems and data sources.
Establish thresholds, KPIs, and alerts for data quality metrics.
2. Root Cause Analysis & Issue Management
Investigate data anomalies and quality incidents using SQL, Python, and Ataccama diagnostics.
Collaborate with data engineers and business analysts to identify and remediate root causes.
Document recurring data issues and contribute to preventive automation solutions.
3. Collaboration & Governance Support
Partner with data stewards, governance, and analytics teams to define and maintain DQ rules and SLAs.
Contribute to metadata enrichment, lineage documentation, and data catalog integration.
Support adoption of DQ frameworks and promote data reliability best practices.
4. Automation & Continuous Improvement
Integrate DQ validations into orchestration tools (Airflow, Databricks Workflows, or ADF).
Leverage Python/Pyspark libraries to complement existing platforms.
Propose process improvements to enhance automation, monitoring, and exception management.
Core Technical Skills
Category
Tools / Skills
Data Engineering & Quality
Databricks (Delta Lake), PySpark, SQL, Python
DQ Platforms
Ataccama ONE / Studio (DQ rules, workflows, profiling)
Orchestration
Apache Airflow, Azure Data Factory, or Databricks Jobs
Data Warehouses
Databricks Lakehouse
Version Control / CI-CD
Git, GitHub Actions, Azure DevOps
Data Catalog / Lineage (Optional)
Collibra, Alation, Ataccama Catalog
Cloud Environments
Azure (preferred), AWS, or GCP
Qualifications & Experience
Bachelor’s degree in Computer Science, Information Systems, Statistics, or related field.
6–9 years of experience in data quality, data engineering, or analytics operations.
Strong command of SQL, Python, and PySpark for data validation and troubleshooting.
Proven experience with Ataccama DQ rule creation and monitoring.
Hands-on exposure to Databricks for building and running data pipelines.
Working knowledge of reconciliation processes, data profiling, and DQ metrics.
Soft Skills & Attributes
Analytical thinker with strong problem-solving abilities.
Detail-oriented and methodical approach to troubleshooting.
Strong communication skills for cross-functional collaboration.
Proactive mindset, capable of owning issues through resolution.
Comfortable balancing hands-on technical work with business stakeholder interaction.
Preferred / Nice to Have
Exposure to data governance frameworks or MDM initiatives.
Familiarity with observability tools (Grafana, Datadog, Prometheus).
Understanding of CI/CD practices for data quality deployment.
Certification in Databricks, Ataccama, or a major cloud platform (Azure/AWS).
Success Indicators
Increase in automated data quality coverage across critical datasets.
Reduction in recurring manual DQ exceptions.
Improved timeliness and accuracy of data available for analytics.
Positive stakeholder feedback on data trust and reliability.
EXPERIENCE
SKILLS
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