Posted:1 week ago|
Platform:
Work from Office
Full Time
Perform data profiling, anomaly detection, and reconciliation across systems and data sources.
Establish thresholds, KPIs, and alerts for data quality metrics.
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.
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.
Integrate DQ validations into orchestration tools (Airflow, Databricks Workflows, or ADF).
Propose process improvements to enhance automation, monitoring, and exception management.
Databricks (Delta Lake), PySpark, SQL, Python
Ataccama ONE / Studio (DQ rules, workflows, profiling)
Apache Airflow, Azure Data Factory, or Databricks Jobs
Databricks Lakehouse
Git, GitHub Actions, Azure DevOps
Collibra, Alation, Ataccama Catalog
Azure (preferred), AWS, or GCP
Bachelor s degree in Computer Science, Information Systems, Statistics, or related field.
Working knowledge of reconciliation processes, data profiling, and DQ metrics.
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.
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).
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.
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, Krak w, Noida, Gurgaon, Mumbai, Pune, and Bengaluru.
Infogain
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