Job Summary

We are seeking a highly skilled and hands-on Lead Data Engineer to design, build, and modernize enterprise-scale data platforms supporting analytics, reporting, and data-driven decision making. This role will lead the technical implementation of cloud-native data solutions using Snowflake, Azure, Python, and Astronomer/Airflow, while partnering with architects, product owners, analytics teams, and business stakeholders to deliver scalable, secure, and high-performing data products.

This is a senior individual contributor role with significant influence on platform architecture, engineering standards, cloud modernization efforts, and data platform strategy.

Key Responsibilities

- Design, build, and optimize scalable enterprise data platforms using Snowflake and Microsoft Azure.
- Develop robust batch, micro-batch, and near real-time data pipelines using Python and Astronomer/Airflow.
- Architect and implement modern cloud data warehouse and data lake solutions.
- Design scalable ELT/ETL frameworks, reusable data ingestion patterns, and data transformation pipelines.
- Leverage advanced Snowflake capabilities including: Streams & Tasks, Dynamic Tables, Snowpark, Iceberg Tables, Secure Data Sharing, and Materialized Views.
- Drive data platform reliability, operational excellence, monitoring, observability, and governance.
- Optimize Snowflake workloads for performance, scalability, and cost efficiency.
- Build and deploy cloud-native solutions using: Azure AKS, Azure Blob Storage, Azure Data Lake Storage, Azure DevOps CI/CD.
- Design and support real-time and event-driven data processing architectures.
- Partner with analytics, reporting, and business teams to provide trusted, analytics-ready data assets.
- Establish engineering best practices, coding standards, and architectural patterns.
- Participate in solution design, technical reviews, and architecture governance activities.





Required Qualifications

- Bachelors or masters degree in computer science, engineering, information systems, or related field.
- 7+ years of experience in Data Engineering, Data Platform Engineering, or Data Warehousing.
- 5+ years of hands-on experience with Snowflake.
- Strong expertise in Python and advanced SQL development.
- Proven experience designing and implementing enterprise-scale data warehouses and analytical platforms.
- Strong experience with Airflow and/or Astronomer for orchestration and workflow management.
- Experience building cloud-native solutions on Microsoft Azure.
- Strong understanding of: Data Modeling, Data Warehousing Concepts, ELT/ETL Frameworks, Distributed Systems, Data Governance, CI/CD and DevOps Practices.
- Excellent analytical, problem-solving, and communication skills.

Technical Skills

Required

- Snowflake
- Python
- SQL
- Airflow / Astronomer
- Azure Cloud Services
- Data Warehousing
- Data Modeling
- Data Lake Architectures
- ELT / ETL Development
- Git
- CI/CD Pipelines

Desired

- Snowpark
- Streams & Tasks
- Dynamic Tables
- Iceberg Tables
- Data Sharing
- CDC Frameworks
- Real-Time Data Processing
- Event-Driven Architectures
- Azure AKS
- Azure Blob Storage
- Azure Data Lake Storage
- Azure DevOps
- REST APIs and Data Integrations

Domain Expertise (Preferred)

- Experience working with Financial Services, Wealth Management, Asset Management, or Investment Analytics platforms.
- Familiarity with:
- Portfolio Management Data
- Holdings & Positions
- Transactions & Tax Lots




- Client Reporting
- Performance Reporting
- Financial Analytics
- Investment Operations Data

Nice to Have

- Experience with up-to-date BI and Analytics platforms such as ThoughtSpot, Power BI, Cognos, Tableau, or similar technologies.
- Familiarity with semantic modeling, dashboard development, self-service analytics, and reporting solutions.
- Experience designing analytics-ready data models to support enterprise reporting and business intelligence workloads.
- Understanding of search-driven analytics, AI-assisted analytics, and embedded analytics capabilities.
- Experience supporting the migration and modernization of legacy BI platforms to cloud-native analytics ecosystems.
- Exposure to data governance, lineage, metadata management, and data catalog solutions.

Preferred Certifications

- SnowPro Core Certification
- SnowPro Advanced Data Engineer
- SnowPro Advanced Architect
- Microsoft Azure
- Microsoft Certified: Azure Data Engineer Associate (DP-203)
- Microsoft Certified: Azure Solutions Architect Expert (AZ-305)
- Microsoft Certified: Azure Fundamentals (AZ-900)

What You'll Bring

- Passion for building modern, scalable cloud data platforms.
- Strong ownership mindset and ability to drive technical initiatives independently.
- Deep technical expertise combined with practical problem-solving skills.
- Ability to influence architecture and engineering decisions across teams.
- Strong collaboration skills with engineers, architects, analysts, and business stakeholders.
- Commitment to engineering excellence, reliability, and continuous improvement.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Lead, Data Engineer (Pune)
🏢 Northern Trust
📍 Pune