Senior Technical Specialist

Datavail Infotech; Mumbai; À distance; INR 3 000 000 - 5 400 000; Plein temps

Résumé du poste

Datavail Infotech in Mumbai, India, is seeking a Senior Azure Data Engineer to design, develop, and modernize enterprise-scale data integration solutions. The role emphasizes hands-on data engineering, SSIS migration to Azure Data Factory, and performance tuning for large datasets.

The ideal candidate has 8+ years of experience in data engineering, ETL development, and data warehousing, with strong SQL Server and T-SQL skills, plus CI/CD and cloud/hybrid platform experience.

Qualifications

• 8+ years of experience in Data Engineering, ETL Development, or Data Warehousing.
• Strong expertise in Microsoft SQL Server and advanced T-SQL development.
• Hands-on with Azure Data Factory (ADF).
• Experience designing and building ETL/ELT pipelines.
• Strong SSIS development, troubleshooting, migration, and modernization.
• Knowledge of data warehouse concepts and dimensional modeling.

Responsabilités

• 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 toward Azure Data Factory and cloud architectures.
• Build and optimize data ingestion, transformation, and integration processes.
• Perform advanced SQL development, query optimization, and performance tuning for large 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 stakeholders to gather requirements and build data solutions.
• Implement CI/CD pipelines and source control best practices for data engineering solutions.
• Support hybrid on-premises and cloud environments.
• Participate in architecture discussions and modernization strategies.

Connaissances

Data Engineering

ETL Development

Data Warehousing

SQL Server

T-SQL

Azure Data Factory

ETL/ELT Pipelines

SSIS

Data Modeling

Dimensional Modeling

Star Schema

Snowflake Schema

REST APIs

SFTP

Data Quality

CI/CD

Git

Hybrid/Cloud Platforms

Formation

Bachelor's Degree

Outils

Azure Data Factory (ADF)

SSIS

Git

CI/CD

Databricks

Snowflake

Azure Synapse Analytics

MongoDB

Description du poste

Title:Senior 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.