Principal, Cloud Data Platform Engineer

ntrs; Pune District; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

Northern Trust is seeking a Principal, Cloud Data Platform Engineer in Pune to design and operate scalable, secure cloud data platforms supporting analytics, ML, and enterprise data needs. You will work with data scientists, analysts, architects, and business stakeholders to deliver modern data capabilities on cloud platforms.

The role requires deep technical expertise, governance, cost-conscious design, and mentoring of engineers while ensuring high performance and reliability across platforms.

Qualifications

• Bachelor's degree in Computer Science, Data Engineering, or related field.
• 15+ years of total work experience in technology infrastructure.
• 10+ years in data, cloud, or platform engineering.
• Hands-on with AWS or Azure.
• Strong experience with big data processing frameworks (e.g., Spark, Databricks, Flink).
• Proven expertise in building data pipelines (Airflow, dbt, Kafka).

Responsibilities

• Design, build, and maintain cloud-native data platforms (AWS/Azure).
• Develop and optimize data pipelines for ingestion, transformation, and processing of diverse data.
• Create reusable frameworks and automation for data workflows and monitoring.
• Ensure data storage, compute, and security are cost-efficient and scalable.
• Collaborate with data scientists, BI teams, and developers to enable analytics and ML workloads.
• Mentor junior engineers and contribute to cloud engineering best practices.

Skills

Cloud architecture

Mentoring

Cross-functional collaboration

Problem solving

Communication

Education

Bachelor's degree in Computer Science/Data Engineering

Master's degree preferred

Tools

Snowflake

Databricks

Flink

Airflow

dbt

Kafka

Docker

Kubernetes

Terraform

CloudFormation / Pulumi

Job description

About Northern Trust

As a global leader in innovative wealth management, asset servicing, asset management and banking services, Northern Trust (Nasdaq: NTRS) is proud to guide the world's most successful individuals, families, corporations and institutions.

Since 1889, we have aligned our efforts with our three guiding Principles That Endure: Service, Expertise, and Integrity. Together, they reflect the three cornerstones of business conduct which we strive to instill in our employees, whom we call partners, and to provide to our clients and the communities we serve worldwide.

With more than 135 years of financial experience and over 24,000 partners, we serve the world's most sophisticated clients using leading technology and exceptional service.

Position : Principal, Cloud Data Platform Engineer

Position Overview

The Principal - Cloud Data Platform Engineer is responsible for designing, building, and maintaining scalable, secure, and high-performance cloud-based data platforms that support analytics, machine learning, and enterprise data needs. This role ensures that data solutions are optimized for performance, cost, and reliability, while meeting governance, compliance, and business requirements. The engineer collaborates closely with data scientists, analysts, architects, and business stakeholders to deliver modern data capabilities on cloud platforms. Should have deep technical expertise, strong design judgment, and the ability to influence without authority.

Platform Engineering & Development

• Design, implement, and maintain cloud-native data platforms (e.g., AWS, Azure).
• Develop and optimize data pipelines for ingestion, transformation, and processing of structured, semi-structured, and unstructured data.
• Build reusable frameworks and automation for data workflows, monitoring, and scaling.
• Ensure data storage and compute solutions are optimized for performance, security, and cost efficiency.
• Integrate cloud data services with enterprise applications, APIs, and third-party tools.

Data Management & Governance

• Implement data quality, lineage, and cataloging solutions across the data platform.
• Enforce governance, security, and compliance standards (e.g., GDPR, HIPAA, SOC2).
• Work with architects and security teams to implement role-based access, encryption, and audit controls.
• Support metadata management, data discoverability, and enterprise-wide data democratization.

Operations & Reliability

• Manage the operational health of the cloud data platform, including monitoring, alerting, and troubleshooting.
• Establish CI/CD pipelines for data services and platform components.
• Implement disaster recovery, backup, and failover strategies.
• Continuously optimize platform performance, cost, and scalability.

Collaboration & Innovation

• Partner with data scientists, BI teams, and application developers to enable advanced analytics and AI/ML workloads.
• Evaluate emerging cloud data services and recommend adoption based on enterprise needs.
• Provide technical expertise in designing cloud-based data architectures and solutions.
• Mentor junior engineers and contribute to best practices in cloud engineering and data development.

Qualifications

• Education & Experience: Bachelor's degree in Computer Science, Data Engineering, or related field (Master's preferred).
• 15+ years of total work experience in technology infrastructure.
• 10+ years of experience in data engineering, cloud engineering, or platform engineering.
• Hands-on experience with at least one major cloud provider (AWS or Azure).
• Strong experience with big data and data processing frameworks (e.g., Spark, Databricks, Flink).
• Proven expertise in building data pipelines with tools like Apache Airflow, dbt, Kafka, or similar.

Skills & Competencies

• In-depth knowledge and experience with Snowflake, Databricks, or similar cloud data platforms.
• Extensive knowledge and real hands-on experience of AI/ML data pipelines and feature engineering.
• Exposure to regulated environments (financial services, healthcare, etc.).
• Proficiency in SQL and one or more programming languages (Python, Java, or Scala).
• Deep understanding of cloud-native data services (e.g., AWS Redshift, Glue, S3, Athena; Azure Synapse, Data Factory; GCP BigQuery, Dataflow).
• Familiarity with containerization and orchestration (Docker, Kubernetes).
• Experience with infrastructure-as-code (Terraform, CloudFormation, Pulumi).
• Knowledge of FinOps principles for cost-efficient data platform design.
• Strong problem-solving, communication, and cross-functional collaboration skills.
• Excellent communication, mentorship, and ability to influence cross-functional teams.

Key Success Metrics

• Uptime, performance, and reliability of the cloud data platform.
• Data availability, quality, and accessibility for business and analytics use cases.
• Efficiency and scalability of data pipelines and processing.
• Cost optimization and resource utilization of cloud data services.