Lead cloud data platform modernization using Snowflake and dbt, migrating legacy SSIS pipelines to ELT architecture.

About the Company

InfoCepts is a global data analytics and consulting firm specializing in data engineering, business intelligence, and cloud modernization. Founded in 2001, the company has grown into a trusted partner for enterprises across North America, Europe, and Asia-Pacific, with delivery centers in India (Pune, Chennai, Bangalore, Nagpur) and offices in the US, UK, and Australia. InfoCepts focuses on accelerating data-driven transformation by building scalable, cloud-native data platforms that empower organizations to make informed decisions. With a strong emphasis on Snowflake, dbt, and modern ELT pipelines, the company serves clients in industries ranging from finance and healthcare to retail and manufacturing.

Role Overview

As a Senior Data Engineer, you will be a key contributor to enterprise-scale cloud data platform initiatives, leading the migration from legacy ETL systems (SSIS) to a modern dbt-driven ELT architecture on Snowflake. This role is ideal for a data engineering professional who is passionate about optimization, standardization, and building reusable frameworks that improve data accessibility, performance, and consistency. You will work closely with cross-functional teams including Snowflake engineers, QA, and client stakeholders to ensure timely and high-quality delivery of transformation workloads.

Key Responsibilities

• Define enterprise dbt architecture standards, including layered transformation strategies, naming conventions, and modular design patterns to support large-scale modernization programs.
• Convert complex SSIS transformations into dbt staging, intermediate, and mart models, ensuring accuracy, maintainability, and alignment with enterprise modeling standards.
• Lead migration strategies from legacy SSIS pipelines to dbt-based ELT frameworks, maintaining consistency, scalability, and performance.
• Develop reusable macros, libraries, and migration accelerators to improve delivery efficiency across multiple transformation streams.
• Define reconciliation strategies, parallel-run validation frameworks, and transformation testing standards for enterprise analytics reliability.
• Collaborate with Snowflake engineering teams to optimize execution strategies, clustering approaches, and warehouse utilization.
• Establish version control standards, CI/CD integration practices, and documentation frameworks for controlled migration execution.
• Maintain transformation documentation, mapping logic, testing evidence, and lineage metadata to support governance and audit readiness.
• Work closely with stakeholders to resolve transformation discrepancies and ensure timely migration delivery.

Tech Stack

• Snowflake (data warehouse, performance optimization)
• dbt (transformation, modeling, data validation)
• SSIS (legacy ETL)
• SQL, dimensional modeling (star schema, snowflake)
• Git / Azure DevOps (version control, CI/CD)
• Terraform (infrastructure automation – desirable)
• Data lineage and governance tools (desirable)
• Data mesh architecture (desirable)

7+ years in data engineering with hands-on dbt and Snowflake experience. Strong in dimensional modeling, CI/CD, and data validation.

Not specified