Posted today · be early
Azure Data Engineer - CTR
Datavail
IndiaremotePosted 1 day ago
Skill Required
Azure-Data-EngineerData-EngineerETL-DeveloperData-Warehouse-EngineerData-Engineering-(Azure)Azure-Data-EngineeringAzure-Data-Platform-EngineerSenior-Azure-Data-EngineerAzure-Data-Platform-EngineeringAzure-Data-Factory-EngineerData EngineerAzureQuery OptimizationData Warehousingdata engineeringtroubleshootingCD pipelinesSQL ServerEngineeringDatabricksanalyticalautomationdevelopingREST APIsShell ScriptingObservabilitySnowflakedesigninganalyticsbuildingMongoDBSparkPythondesignOpenAPICI/CDFulltime
Key highlights
- Experience Level: 10+
- Location: India (Remote)
- Key Requirement: Strong Azure Data Factory (ADF) and SQL Server expertise
- Working Hours: Overlap with North America (up to 3-4 PM ET)
Role overview
We are seeking a highly skilled, hands-on Senior Data Engineer with strong expertise in SQL Server, Azure Data Factory (ADF), ETL development, and Data Warehousing. This role is focused on designing, developing, troubleshooting, and modernizing enterprise-scale data integration solutions, specifically driving the modernization of legacy SSIS-based workloads to Azure-based data platforms. The ideal candidate is a true Data Engineer, not primarily a BI or reporting developer, capable of independently analyzing pipelines and building scalable solutions.
Responsibilities
- Design, develop, and maintain scalable ETL/ELT solutions and data pipelines.
- Support and enhance enterprise data warehouse solutions.
- Analyze existing SSIS packages and lead modernization efforts toward Azure Data Factory and modern cloud-based architectures.
- Build and optimize data ingestion, transformation, and integration processes.
- Perform advanced SQL development, query optimization, and performance tuning for large-volume datasets.
- Develop integrations with REST APIs, third-party systems, and file-based interfaces.
- Support SFTP-based and batch data exchange processes.
- Troubleshoot production issues, perform root-cause analysis, and implement preventive solutions.
- Ensure data quality through reconciliation, validation, monitoring, and exception handling.
- Collaborate with business and technical stakeholders to gather requirements and build data solutions.
- Implement CI/CD pipelines and source control best practices for data engineering solutions.
- Support hybrid environments involving on-premises and cloud-based systems.
- Participate in architecture discussions and recommend modernization strategies.
Requirements
- Bachelor’s Degree
- 10+ years of experience (Experience Level)
- 8+ years of experience in Data Engineering, ETL Development, or Data Warehousing.
- Strong expertise in Microsoft SQL Server and advanced T-SQL development.
- Strong hands-on experience with Azure Data Factory (ADF).
- Extensive experience designing and building ETL/ELT pipelines.
- Strong experience with SSIS development, troubleshooting, migration, and modernization.
- Solid understanding of Data Warehouse concepts and dimensional modeling, including: Fact & Dimension models, Star Schema, and Snowflake Schema
- Experience processing large-volume data and performing SQL performance tuning.
- Experience integrating with REST APIs and external data providers.
- Experience with SFTP and file-based integrations.
- Strong knowledge of data validation, reconciliation, and quality controls.
- Proven production support and troubleshooting skills.
- Experience using Git, source control practices, CI/CD, and deployment automation.
- Experience working across on-premises, hybrid, and cloud data platforms.
- Highly hands-on and technically strong in data engineering.
- Ability to work independently with minimal supervision.
- Ability to quickly understand and troubleshoot complex legacy and modern data platforms.
- Strong analytical and problem-solving skills.
- Experience supporting mission-critical production environments.
- Comfortable driving modernization initiatives and recommending best practices.
- Effective communication skills with both technical and business stakeholders.
- Ability to take ownership of deliverables and operational outcomes.
Nice to have
- Exposure to AI-enabled data engineering solutions.
- Experience incorporating AI/GenAI capabilities into data engineering solutions.
- Experience with Azure OpenAI Service or OpenAI API integrations.
- Python-based AI automation and intelligent workflow development.
- AI-assisted data quality monitoring, anomaly detection, and operational troubleshooting.
- Understanding of: Retrieval-Augmented Generation (RAG), Embeddings, and Vector Databases
- Python
- PySpark
- Databricks
- Snowflake
- Azure Synapse Analytics
- Microsoft Fabric
- MongoDB / NoSQL databases
- PowerShell scripting
- Data Lake and Lakehouse architectures
- Industry Experience: Enterprise Data Warehousing
- Industry Experience: Financial Services
- Industry Experience: Healthcare
- Industry Experience: Retail & Consumer Data Platforms
- Industry Experience: SaaS and Cloud-Native Data Environments
Additional details
- Title: Azure Data Engineer
- Location: India ( Remote )
- Resources must provide overlap with North America business hours, ideally until approximately 3:00 PM–4:00 PM Eastern Time (ET).
- Resources may work staggered shifts to ensure broader support coverage and operational continuity.
- Originally posted on Himalayas
