ROLES RESPONSIBILITIES Key Responsibilities 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 DQ Tools Ataccama DQMS Informatica DQ Collibra basic exposure Data Platforms Databricks Azure Synapse Snowflake Data Engineering SQL PySpark Python Integration Automation Azure Data Factory Airflow APIs Visualization Monitoring Power BI ServiceNow for issue tracking Governance Quality Management Metadata management data lineage tracking KPI reporting 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 Solid 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 6-8 Years SKILLS Primary Skill Data Engineering Sub Skill s Data Engineering Additional Skill s Python databricks SQL Azure Data Factory ABOUT THE COMPANY Infogain is a human-centered digital platform and software engineering company based out of Silicon Valley We engineer business outcomes for Fortune 500 companies and digital natives in the technology healthcare insurance travel telecom and retail CPG industries using technologies such as cloud microservices automation IoT and artificial intelligence We accelerate experience-led transformation in the delivery of digital platforms Infogain is also a Microsoft NASDAQ MSFT Gold Partner and Azure Expert Managed Services Provider MSP Infogain an Apax Funds portfolio company has offices in California Washington Texas the UK the UAE and Singapore with delivery centers in Seattle Houston Austin Krakow Noida Gurgaon Mumbai Pune and Bengaluru

📌 Azure Data Engineer (senior) (Karnataka)
🏢 Infogain
📍 Karnataka