Title: Azure Data Engineer
Location: India ( Remote )
Education: Bachelor’s Degree
Experience Level: 10+
We are looking for experienced Data Engineers who can provide overlap with North America business hours. The ideal coverage is until approximately 3:00 PM–4:00 PM Eastern Time (ET). Resources may also work staggered shifts to ensure broader support coverage and operational continuity.
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. The ideal candidate is a true Data Engineer, not primarily a BI or reporting developer. They should be capable of independently analyzing existing data pipelines, resolving production issues, building scalable data solutions, and driving the modernization of legacy SSIS-based workloads to Azure-based data platforms.
Required Qualifications:
Technical Skills
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
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.
Preferred AI / GenAI Experience:
Candidates with exposure to AI-enabled data engineering solutions will be highly valued.
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
Vector Databases
Additional Preferred Skills:
Python
PySpark
Databricks
Snowflake
Azure Synapse Analytics
Microsoft Fabric
MongoDB / NoSQL databases
PowerShell scripting
Data Lake and Lakehouse architectures
Desired Candidate Profile
The successful candidate will:
Be highly hands-on and technically strong in data engineering.
Demonstrate the ability to work independently with minimal supervision.
Quickly understand and troubleshoot complex legacy and modern data platforms.
Possess strong analytical and problem-solving skills.
Have experience supporting mission-critical production environments.
Be comfortable driving modernization initiatives and recommending best practices.
Communicate effectively with both technical and business stakeholders.
Take ownership of deliverables and operational outcomes.
Nice-to-Have Industry Experience:
Enterprise Data Warehousing
Financial Services
Healthcare
Retail & Consumer Data Platforms
SaaS and Cloud-Native Data Environments
Key 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.
About UsDatavail is a leading provider of data management, application development, analytics, and cloud services, with more than 1,000 professionals helping clients build and manage applications and data via a world-class tech-enabled delivery platform and software solutions across all leading technologies. For more than 17 years, Datavail has worked with thousands of companies spanning different industries and sizes, and is an AWS Advanced Tier Consulting Partner, a Microsoft Solutions Partner for Data & AI and Digital & App Innovation (Azure), an Oracle Partner, and a MySQL Partner. About the Team
Skills Required
- Bachelor's degree
- 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
- Extensive experience designing and building ETL/ELT pipelines
- Strong SSIS development, troubleshooting, migration, and modernization experience
- Understanding of data warehousing and dimensional modeling, including fact and dimension models, star schemas, and snowflake schemas
- Experience processing large-volume data and performing SQL performance tuning
- Experience integrating REST APIs and external data providers
- Experience with SFTP and file-based integrations
- Knowledge of data validation, reconciliation, and quality controls
- Production support and troubleshooting experience
- Experience with Git, source control, CI/CD, and deployment automation
- Experience across on-premises, hybrid, and cloud data platforms
- Python
- PySpark
- Databricks
- Snowflake
- Azure Synapse Analytics
- Microsoft Fabric
- MongoDB or NoSQL databases
- PowerShell scripting
- Data Lake and Lakehouse architecture experience
- AI or GenAI data engineering experience, including Azure OpenAI Service or OpenAI API integrations
- Python-based AI automation and intelligent workflow development
- Experience with AI-assisted data quality monitoring, anomaly detection, or operational troubleshooting
- Understanding of RAG, embeddings, and vector databases
Datavail Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Datavail and has not been reviewed or approved by Datavail.
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Fair & Transparent Compensation — Pay is considered competitive for many roles at the time of hire, with some noting significant initial increases and timely pay. Feedback suggests compensation can be strong in particular regions or positions even as overall satisfaction varies.
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Wellbeing & Lifestyle Benefits — Remote-friendly roles and flexible or unlimited time off policies are highlighted as part of the employment experience. Feedback suggests these arrangements support work flexibility, though experiences differ by team and location.
Datavail Insights
What We Do
A premiere data services company serving clients in North America, Datavail has 1,000 data professionals, data engineers, developers, project managers, consultants, and business experts, supported by industry-leading automation and intellectual property. For more than 17 years, Datavail has worked with thousands of companies spanning different industries and sizes. At Datavail, we look for more than smarts, experience and proficiency. On top of those requirements, we seek people who mesh with our corporate values. We seek brilliance without bravado and know-how without a know-it-all attitude. We hold low ego in high regard, embrace problem-solving as a passion and welcome every day as a new opportunity to learn. We’re flexible and hard working. We’re committed to our clients and colleagues. We help our people grow so they can help our clients grow. That makes us grow so we can help even more customers leverage organizational data for business value. Our Core Values: 1. We desire to serve. 2. We embody flexibility for availability 3. We exemplify low ego. 4. We work hard. 5. We strive for continuous improvement. 6. We are growth-oriented.
