Data Engineer - Associate Director

KPMG Global Services; Bengaluru; On-site; INR 2,000,000 - 3,000,000; Full time

Benefits offered by this job

Parental leave

Employee development programs

Networking opportunities

Job summary

KPMG Global Services is seeking a Databricks Data Architect Associate Director to lead the design and implementation of scalable data platforms on Azure. The ideal candidate will have more than 12 years of experience in data engineering and hands-on expertise in Databricks, Apache Spark, and Azure services.

This leadership role requires strong communication skills for stakeholder engagement, technical mentoring, and ensuring data quality. A collaborative and growth-oriented environment with diverse benefits awaits the right candidate.

Qualifications

• 12+ years of overall experience in data engineering.
• Extensive hands-on experience with Databricks and Apache Spark.
• Proven experience designing large-scale data ingestion pipelines.

Responsibilities

• Architect and deliver scalable data platforms using Azure Databricks.
• Build efficient data ingestion and transformation pipelines.
• Implement data security and privacy controls.

Skills

Databricks

Apache Spark

Azure services

PySpark

SQL

Scala

CI/CD

DevSecOps

Education

Bachelor's or higher degree in Computer Science or related discipline

Tools

Azure DevOps

Terraform

Power BI

Job description

Databricks Data Architect Associate Director

Location: Bengaluru, India
Employment Type: Full-time
Reporting To: Jagadish Doki
Organization: KPMG Global Services (KGS)

The Databricks Data Architect Associate Director will play a critical leadership role in designing, building, and scaling enterprise‑grade data platforms using Databricks on Azure. This role is responsible for architecting robust data ingestion and transformation frameworks, enabling secure and governed data lakes, supporting cloud migration programs, and providing technical leadership across large, complex data engineering initiatives.

The role combines deep hands‑on expertise, solution architecture, and stakeholder engagement, making it ideal for a senior data engineering leader who can translate business objectives into scalable technical solutions while mentoring teams and driving best practices.

Key Responsibilities

• Architect, design, and deliver scalable data platforms using Azure Databricks, Apache Spark, and Delta Lake.
• Build and optimize end‑to‑end data ingestion, processing, and transformation pipelines for large, complex datasets from multiple sources.
• Develop reusable and standardized frameworks to improve performance, reliability, and maintainability of data engineering workloads.
• Lead and support cloud migration initiatives, including modernization of legacy data platforms to Databricks and Azure native services.
• Implement data security, governance, and privacy controls, ensuring compliance with enterprise and regulatory standards.
• Monitor, troubleshoot, and performance‑tune Databricks workloads with a focus on cost and compute efficiency.
• Collaborate closely with business stakeholders, analytics teams, and cross‑functional technology teams to ensure data quality and availability.
• Provide technical thought leadership, defining architecture standards, patterns, and best practices for Databricks adoption.
• Deliver proofs of concept (PoCs) and solution demos to showcase Databricks capabilities to stakeholders and clients.
• Mentor and guide data engineers, promoting high engineering standards and continuous improvement.

Mandatory Skills & Experience

• Bachelors or higher degree in Computer Science, Information Technology, or related discipline, with 12+ years of overall experience.
• Extensive hands‑on experience with Databricks and Apache Spark, including PySpark, SQL, and Scala.
• Strong expertise in designing large‑scale data ingestion and transformation pipelines.
• Proven experience working with Azure services, including Azure Databricks, Azure Data Lake Storage, and Azure Blob Storage.
• Solid understanding of cloud architectures and data engineering migration methodologies.
• Experience implementing CI/CD and DevSecOps practices in Databricks environments.
• Knowledge of big data file formats such as Parquet and Avro, along with compression techniques.
• Strong communication skills with the ability to explain complex technical concepts to both technical and non‑technical audiences.
• Demonstrated ability to work independently, take ownership, and drive outcomes.

Preferred Qualifications

• Hands‑on experience with Azure DevOps, Terraform, and Microsoft VSTS.
• Experience integrating Databricks with Azure Data Factory for orchestration.
• Familiarity with Power BI for analytics and reporting use cases.
• Understanding of Azure RBAC and IAM concepts for securing data platforms.
• Relevant certifications such as Databricks Certified Data Engineer or DP203: Data Engineering on Microsoft Azure.
• Exposure to AI/ML workloads and their integration with Databricks platforms.

Culture & Benefits

• Collaborative, inclusive, and growth‑oriented environment with benefits that support personal and professional wellbeing, including parental leave, CSR initiatives, networking opportunities, and employee development programs.
• Benefits may vary by role and location.