Data Engineer Advisor

NTT America, Inc.; Hyderabad; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

NTT America, Inc. in Hyderabad seeks a Hands-On Data Tech Lead with 8–10 years of SSIS, SQL Server, and Azure Databricks experience to drive modernization and scaling of the data platform. You will lead migrations, architect MDW/Delta Lake, and actively write code.

You will mentor engineers, collaborate with analytics and DevOps, and build end-to-end ELT/ETL pipelines using PySpark in cloud and on-prem environments.

Qualifications

• 8–10 years of experience with SSIS, SQL Server, Azure Databricks and PySpark.
• Hands-on data lead responsible for technical leadership and coding.
• Experience migrating SSIS to cloud-native Azure Databricks/PySpark Lakehouse.

Responsibilities

• Lead migration of legacy SSIS packages to Azure Databricks/PySpark environments.
• Architect end-to-end Modern Data Warehouse (MDW) and Delta Lake architecture on Azure.
• Mentor and guide a team of data engineers with code reviews and standards.
• Collaborate with Data Architects, Business Analysts, and DevOps to translate requirements into blueprints.
• Develop and optimize scalable ETL/ELT pipelines using PySpark on Azure Databricks.
• Refactor on-prem SSIS packages and T-SQL code to ensure business continuity.
• Implement Delta Lake features including schema evolution and time-travel queries.
• Orchestrate workloads by integrating Azure Data Factory with on-prem databases and ADLS Gen2.
• Optimize Spark configurations to reduce compute overhead and runtime.
• Enforce data quality with automated validation, auditing and reconciliation.
• Implement CI/CD automations via Azure DevOps or GitHub Actions.

Skills

Azure Databricks

Delta Lake

PySpark

Python

SSIS

SQL Server

Azure Data Factory

CI/CD

Git

Data Modeling

Tools

Azure Data Factory

SSIS

Job description

India T&M Special Bonus:

Job Summary

A highly skilled 8 to 10 years of experience on SSIS. SQL Server, Azure Databricks, Pyspark, Hands-On Data Tech Lead to drive the modernization and scaling of our enterprise data platform to provide technical leadership while remaining deeply technical and actively writing code. Also lead the migration, integration, and development of data pipelines across our legacy SQLServer/SSIS environments and our modern cloud infrastructure built on Azure Databricks and PySpark and act as the principal architect and developer for end-to-end ELT/ETL pipelines, ensuring optimal performance, data governance, and scalability.

• Lead the migration of legacy SQL Server Integration Services (SSIS) packages to modern, cloud-native Azure Databricks / PySpark Lakehouse environments.

• Architect end-to-end Modern Data Warehouse (MDW) and Medallion architecture systems (Bronze, Silver, Gold layers) within Azure.

• Mentor and guide a team of data engineers, conducting stringent code reviews, enforcing design patterns, and establishing development standards.

• Collaborate with stakeholders including Data Architects, Business Analysts, and DevOps teams to translate complex business requirements into technical blueprints.

• Develop and optimize scalable, modular, high-performance batch and real-time ETL/ELT pipelines using PySpark on Azure Databricks cluster environments.

• Maintain and refactor existing on-premise SSIS packages and complex T-SQL code (stored procedures, views, performance tuning) to ensure business continuity during transition phases.

• Implement Delta Lake features, managing transactions, schema evolution, and time-travel querying functionalities.

• Orchestrate workflows seamlessly by integrating Azure Data Factory (ADF) with on-premise databases, cloud storage (ADLS Gen2), and Databricks activities.

• Optimize Spark configurations and cluster utilization to drastically reduce cloud compute overhead and job execution windows.

• Enforce data quality frameworks encompassing automated data validation, error reconciliation, and operational audit logging.

• Implement CI/CD automations via Azure DevOps or GitHub Actions to manage environments, code repositories (Git), and deployment pipelines.

Skill Requirements

Technical Skills

• Azure Big Data Stack: Deep, production-level knowledge of Azure Databricks, Delta Lake, Unity Catalog, and Azure Data Lake Storage (ADLS Gen2).

• Programming Languages: Advanced proficiency in Python and PySpark core APIs (Spark SQL and DataFrames).

• Legacy ETL & Databases: Mastery of SQL Server, Advanced T-SQL writing, and extensive experience configuring, deploying, and troubleshooting SSIS packages.

• Orchestration: Hands-on experience mapping dependencies and scheduling triggers using Azure Data Factory (ADF).

• Data Modeling: Expert understanding of relational (OLTP) and dimensional (OLAP) schemas, explicitly Star and Snowflake architectures.

• DevOps & Security: Competency with Git branching, CI/CD automated release deployments, and secure data handling mechanisms (Azure Key Vault, network isolation).

Soft Skills & Leadership

• Proven track record as a coding lead who splits time between management/design and hands-on execution.

• Excellent cross-functional communication skills, comfortably discussing data strategies with both executive leaders and junior technical staff.

• Strong debugging and root-cause analysis (RCA) skills for multi-tier platform failures.

• Preferred Certifications: Microsoft Certified: Azure Data or Databricks