Project description

The project is for one of the world's famous science and technology companies in pharmaceutical industry, supporting initiatives in AWS, AI and data engineering, with plans to launch over 20 additional initiatives in the future. Modernizing the data infrastructure through the transition to Snowflake as a priority, as it will enhance capabilities for implementing advanced AI solutions and unlock numerous opportunities for innovation and growth. We are seeking a Lead data engineer who will design, develop, and lead Snowflake-based data solutions using DBT, with responsibility for a small team of 3, and for coordinating with the Project Lead for status updates and with business stakeholders for architecture decisions. The role also entails producing high-level documentation to understand development complexity and to enable accurate team assignment and timeline estimation.

Responsibilities

Develop and maintain scalable Snowflake data solutions and DBT transformations. Lead a team of resources: assign tasks, perform code reviews, mentor, and manage performance.

Collaborate with the project Lead to provide regular status updates and escalate issues as needed.

Engage with business stakeholders to define architecture, data models, data flow, and integration patterns.

Produce high-level architecture documents outlining scope, components, interfaces, risks, and complexity to support allocation and timelines.

Define and manage project timelines, milestones, and estimates; translate requirements into a practical development plan.

Ensure data quality, governance, security, and compliance across pipelines.

Establish CI/CD pipelines for Snowflake/DBT deployments (preferably using Azure DevOps or equivalent).

Implement robust testing strategies: unit tests, data quality checks, and validation processes.





Create and maintain documentation for data models, data lineage, and development standards.

Identify performance bottlenecks, optimize Snowflake queries and DBT models, and implement best practices.

Collaborate across teams (data engineering, analytics, product) to ensure alignment with business goals.

Valuable to have basic to mid-level knowledge of AWS and Streamlit

Skills

Must have 12–15 years of overall experience in data engineering, with a minimum of 6–7 years of relevant and hands-on expertise in Snowflake and DBT.

Proficiency in using Fivetran for automated ELT data ingestion, with experience in integrating Fivetran pipelines with dbt and Snowflake for scalable data solutions.

Strong SQL proficiency and advanced Python skills for data processing and automation.

Deep expertise in Snowflake architecture, performance tuning, and data modeling (OLTP/OLAP/Data Vault 2.0).

Extensive experience building and operating DBT-based pipelines and managing DBT projects.

Experience with CI/CD and release management; familiarity with Azure DevOps or similar toolchains.

Familiarity with IaC concepts and tools (Terraform, CloudFormation).

Demonstrated leadership experience: mentoring junior developers, running small teams, and stakeholder management.

Excellent communication skills and ability to convey complex concepts to non-technical stakeholders.

Exposure to cloud platforms (AWS, Azure, GCP) and data governance concepts.

Nice to have

Experience with additional analytics and data technologies; knowledge of streaming data (e.g., Apache Kafka) is a plus.

Prior experience in architecture documentation and creating detail-level or high-level design artifacts.

Other

Languages

English: B2 Upper Intermediate

Seniority

Lead

Bengaluru, India

Req. VR-124315

DWH Development

Cross Industry Solutions

03/08/2026

Req. VR-124315

📌 Lead Snowflake Data Engineer (Bengaluru)
🏢 Luxoft
📍 Bengaluru