Azure Data Engineer Senior

Roles & Responsibilities

Key Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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

• 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, Kraków, Noida, Gurgaon, Mumbai, Pune, and Bengaluru.

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