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About the role
As an experienced Data Professional supporting Azure-based data platform, analytics, reporting, and advanced analytics and science work, your responsibilities will include: - Designing, building, and maintaining data pipelines using Azure Data Factory, Azure Data Lake Gen2, Synapse, Fabric, and Databricks. - Ingesting, transforming, and validating data from multiple business systems, APIs, databases, and files. - Developing and maintaining data models, source-to-target mappings, business rules, and data quality checks. - Performing data profiling, reconciliation, gap analysis, and root-cause analysis. - Writing complex SQL, Python, PySpark, and KQL queries for data processing and analysis. - Building and supporting Power BI dashboards, reports, semantic models, KPIs, and analytical datasets. - Applying statistical analysis, forecasting, anomaly detection, and basic machine learning techniques where needed. - Supporting Dev/UAT/Prod deployments, CI/CD, documentation, testing, and stakeholder sign-off. - Ensuring data security, governance, RBAC, access control, and performance best practices. Your skills should include: - 5+ years of experience in data engineering, data analytics, BI, or data science. - Strong hands-on experience with Azure data services. - Strong skills in SQL, Python, PySpark, Power BI, and data modeling. - Experience with ADF, ADLS Gen2, Synapse/Fabric, Databricks, dbt, or Airbyte. - Ability to translate business requirements into technical specifications, data models, reports, and analytics solutions. - Experience with data validation, documentation, UAT support, and stakeholder communication. - Knowledge of Azure DevOps, Git, CI/CD, and Agile delivery is preferred. Qualifications required for this role: - Bachelors or Masters degree in Computer Science, Data Science, Information Technology, Engineering, Statistics, or a related field. Please note that the working hours for this position are Night (IST)/PST. As an experienced Data Professional supporting Azure-based data platform, analytics, reporting, and advanced analytics and science work, your responsibilities will include: - Designing, building, and maintaining data pipelines using Azure Data Factory, Azure Data Lake Gen2, Synapse, Fabric, and Databricks. - Ingesting, transforming, and validating data from multiple business systems, APIs, databases, and files. - Developing and maintaining data models, source-to-target mappings, business rules, and data quality checks. - Performing data profiling, reconciliation, gap analysis, and root-cause analysis. - Writing complex SQL, Python, PySpark, and KQL queries for data processing and analysis. - Building and supporting Power BI dashboards, reports, semantic models, KPIs, and analytical datasets. - Applying statistical analysis, forecasting, anomaly detection, and basic machine learning techniques where needed. - Supporting Dev/UAT/Prod deployments, CI/CD, documentation, testing, and stakeholder sign-off. - Ensuring data security, governance, RBAC, access control, and performance best practices. Your skills should include: - 5+ years of experience in data engineering, data analytics, BI, or data science. - Strong hands-on experience with Azure data services. - Strong skills in SQL, Python, PySpark, Power BI, and data modeling. - Experience with ADF, ADLS Gen2, Synapse/Fabric, Databricks, dbt, or Airbyte. - Ability to translate business requirements into technical specifications, data models, reports, and analytics solutions. - Experience with data validation, documentation, UAT support, and stakeholder communication. - Knowledge of Azure DevOps, Git, CI/CD, and Agile delivery is preferred. Qualifications required for this role: - Bachelors or Masters degree in Computer Science, Data Science, Information Technology, Engineering, Statistics, or a related field. Please note that the working hours for this position are Night (IST)/PST.