Data Engineer Advisor

NTT DATA, Inc.; Hyderabad; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

NTT DATA, Inc. is seeking an experienced Hands-On Data Tech Lead in Hyderabad with 8–10 years of experience to drive modernization and scaling of the enterprise data platform.

You will provide technical leadership while actively writing code, migrating legacy SSIS to cloud-native Databricks/PySpark, and shaping end-to-end ELT/ETL pipelines. You will architect the MDW with Bronze/Silver/Gold layers, mentor a team, collaborate with analytics and DevOps, and optimize Spark performance in a

Qualifications

• 8–10 years of data engineering experience with SSIS and modern Azure data platforms.
• Proven track record as a hands-on data tech lead.
• Strong skills in data modeling, ETL/ELT design, and performance tuning.
• Experience migrating on-prem SSIS to cloud-based Databricks/PySpark.

Responsibilities

• Lead migration of legacy SSIS packages to cloud-native Azure Databricks/PySpark Lakehouse.
• Architect end-to-end Modern Data Warehouse (MDW) with Bronze/Silver/Gold layers in Azure.
• Mentor and guide a team of data engineers, enforcing standards.
• Collaborate with Data Architects, BAs, and DevOps to translate requirements.
• Develop and optimize scalable ETL/ELT pipelines using PySpark on Databricks.
• Maintain and refactor on-prem SSIS and T-SQL code for continuity.
• Implement Delta Lake features, schema evolution, and time-travel queries.
• Orchestrate workflows by integrating ADF with on-prem and cloud data stores.
• Optimize Spark configs to reduce compute costs and runtimes.
• Enforce data quality with automated validation, reconciliation, and audit logging.
• Implement CI/CD automations via Azure DevOps or GitHub Actions.

Skills

Data leadership

Mentoring team

Cross-functional communication

Debugging & RCA

Coding lead

Tools

Azure Databricks

PySpark

SSIS

SQL Server

Azure Data Factory

Delta Lake

Unity Catalog

ADLS Gen2

Job description

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).
• 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

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