Specialist - Data Engineering

Ltm • Media & Entertainment • Creative Agencies • SQL • Azure Data Factory • 7 hours ago
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Salary
≈ $101k – $192k per year (Estimated)
Location
In office (Cleveland)
Seniority
Senior · 6+ years exp

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Oct 7, 2026. Ltm scores B on the Alion truth index.

Overview
Company
Impact
Profile match

Ltm

LTIMindtree is a worldwide technology consulting and digital solutions company that empowers businesses in a variety of sectors to get to the future faster by combining engineering DNA and tech expertise.
ltm.com • Bengaluru • Mumbai • Hyderabad • Chennai • Pune • Branding • Creative Agencies • Media & Entertainment • Enterprise Apps Implementation Partners • IT Outsourcing & Dedicated Teams • IT Consulting & Digital Transformation • Est. 1996
Tech stack of Ltm

Job Summary

We are seeking a Senior Snowflake Developer with at least 6 years of experience to design, develop, and optimize secure, scalable data solutions. The ideal candidate will have hands-on expertise in Snowflake, Snowflake data products, COCO, Snowflake AI/ML, Azure Data Factory, Azure Data Lake Storage Gen2, SQL, and DevOps practices, with the ability to lead development independently.

Key Responsibilities

·Snowflake solution development: Design, develop, and implement secure, scalable Snowflake data solutions with a focus on performance, reliability, and efficient resource utilization.

·Data pipelines and integration: Build, configure, and manage Azure Data Factory pipelines for data ingestion, transformation, and loading across Azure SQL Database, Azure Data Lake Storage Gen2, and Snowflake.

··Data migration and environment management: Support data transformation and migration initiatives, including production-to-lower-environment Snowflake refreshes, while maintaining data accuracy and operational efficiency.

··SQL and performance optimization: Develop and tune complex SQL queries, monitor platform performance, and optimize workloads and resource consumption.

·Data quality and monitoring: Implement data-quality checks, operational monitoring, and appropriate metrics to identify issues and maintain reliable data processing.

·DevOps and automation: Automate data pipelines and code deployments using CI/CD tools, troubleshoot issues within the data-operations environment, and support dependable releases.

·Collaboration and independent delivery: Work with data architects, analysts, and other team members to translate requirements into effective solutions while independently driving development activities.

·Troubleshooting: Diagnose and resolve issues across Snowflake solutions, data pipelines, and integration processes.

·Documentation: Maintain clear documentation for architectures, data designs, pipelines, processes, and operational procedures to support maintainability and knowledge sharing.

Mandatory Skills

·Snowflake

·Snowflake AI/ML

·Snowflake Data Science

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