Senior Snowflake Lead - Data Engineering
First seen by Alion on Aug 27, 2026.
Company Overview:
Devlats Pvt Ltd is a technology-driven organization specializing in advanced data engineering solutions and cloud transformation services. We partner with global enterprises to architect scalable data ecosystems that drive actionable insights and operational efficiency. Operating at the intersection of cloud infrastructure and big data analytics, we empower businesses to modernize their data stacks, ensuring high performance, security, and agility in a rapidly evolving digital landscape.
Role Overview:
As a Senior Snowflake Lead, you will serve as the technical authority for our data engineering initiatives, overseeing the design and implementation of robust, cloud-native data platforms. You will collaborate closely with cross-functional engineering teams, product managers, and key stakeholders to translate complex business requirements into scalable data architectures. Your work will directly influence the efficiency of our data pipelines and the reliability of the analytics platforms that support our clients' critical decision-making processes. This is a fully remote position requiring high levels of autonomy and technical leadership.
Key Responsibilities:
- Architect and maintain high-performance data warehouses on Snowflake to ensure seamless data accessibility and optimal query performance for end-users.
- Lead the end-to-end development of complex ETL/ELT pipelines using PySpark and Databricks to streamline data ingestion and transformation processes.
- Design sophisticated data models that align with business logic, ensuring data integrity and consistency across the enterprise ecosystem.
- Implement comprehensive automation testing frameworks to validate data quality and pipeline reliability, minimizing downtime and manual intervention.
- Mentor junior engineers and conduct code reviews to maintain high standards of engineering excellence and technical best practices.
- Collaborate with cloud infrastructure teams to optimize AWS and Azure environments for cost-efficiency and security compliance.
Required Skillset:
- Demonstrated expertise in architecting and managing large-scale Snowflake environments with a deep understanding of data warehousing principles.
- Proven ability to develop and optimize data processing workflows using Python, PySpark, and Databricks within distributed computing environments.
- Strong proficiency in designing complex data models and implementing robust ETL strategies that support high-volume data traffic.
- Extensive experience working with cloud platforms, specifically AWS and Azure, to deploy and scale data solutions.
- Exceptional problem-solving skills with the ability to communicate technical strategies effectively to both technical and non-technical stakeholders.
- A minimum of 10 to 13 years of professional experience in data engineering, with a track record of leading technical projects in a remote or distributed team environment.
- Ability to thrive in a remote-first culture, demonstrating self-discipline, proactive communication, and the ability to manage complex deliverables independently.
Skills
Data Engineering, Snowflake DB, PySpark, Databricks, AWS, Azure, Data Warehousing, Data Ingestion, Distributed Computing