Senior Data Engineer and Technical Lead

NTT DATA Global Delivery Services Ltd; Hyderabad; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

NTT DATA Global Delivery Services Ltd is seeking a highly skilled Data Engineer Advisor with 8 to 10 years of experience to drive modernization and scaling of our enterprise data platform. You will provide technical leadership while remaining hands-on, migrating legacy SSIS to Azure Databricks and PySpark, and architecting a modern data warehouse across Bronze/Silver/Gold layers.

You will mentor a team of engineers, enforce design patterns, and collaborate with Data Architects, Business

Qualifications

• 8-10 years of experience in data engineering and data platforms.
• Strong hands-on expertise with SSIS, SQL Server, and modern cloud data stacks.

Responsibilities

• Lead migration of SSIS packages to Azure Databricks/PySpark Lakehouse environments.
• Architect end-to-end Modern Data Warehouse and Medallion architectures (Bronze, Silver, Gold).
• Mentor data engineers, conduct code reviews, and enforce development standards.
• Develop scalable batch and real-time ETL/ELT pipelines using PySpark on Azure Databricks.
• Collaborate with Data Architects, BI analysts, and DevOps to translate business requirements into blueprints.
• Implement Delta Lake features, schema evolution, and time-travel querying.
• Orchestrate workflows with Azure Data Factory and on-premise/cloud storage integrations.
• Establish CI/CD automations via Azure DevOps or GitHub Actions.

Skills

Azure Databricks

Python

PySpark

SQL

T-SQL

Delta Lake

Data Governance

CI/CD

Azure Data Factory

Git

RCA

Data Modeling

DevOps

Security

Tools

SQL Server

SSIS

Azure DevOps

Git

ADLS Gen2

Job description

Data Engineer Advisor 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 Experience Level Senior Level