Job Description:

Role Title: Snowflake Data Engineer Role

Position Type: Contract (3-6 months)

Location: India

Role Overview:

We are seeking an experienced Data Engineer to support a high-priority data integration and cloud enablement initiative. The primary focus of this role is designing and executing end-to-end ELT pipelines and data transfer workflows migrating structured data from SQL sources into Snowflake and orchestrating bulk file transfers into Azure Data Lake Storage (ADLS).

Responsibilities:

- Design, build, and maintain scalable ELT/ETL pipelines and data workflows for ingestion and transformation.

- Execute structured data extraction, movement, and landing from relational SQL databases directly into Snowflake staging and core layers.

- Build, execute, and monitor file movement tasks to efficiently transfer flat files, logs, or unstructured formats into Azure Data Lake Storage (ADLS).

- Write and tune high-performance SQL queries for data modeling, validation, data verification, and staging transformations.

- Conduct data reconciliation and completeness checks to ensure zero loss across data pipelines during bulk migration.

- Collaborate closely with the Lead Data Integration Expert and client engineering teams to align with platform connectivity, security, and governance protocols.

Required Skills:

- ELT / Data Pipelines: Proven, hands-on experience building, optimizing, and monitoring production ELT/ETL pipelines and data workflows.

- SQL & Relational Databases: Strong proficiency in SQL (writing complex queries, performance tuning, indexing) for extracting and validating large datasets across relational engines.

- Snowflake: Hands-on experience loading and modeling data in Snowflake using staging strategies, COPY commands, or bulk loading utilities.

- Azure Cloud Storage: Solid background working with Azure Data Lake Storage (ADLS Gen2), Blob Storage, and associated file transfer/ingestion patterns.

- File Processing: Practical experience with bulk file ingestion formats (CSV, Parquet, JSON) and file movement tooling.

- Agile Execution: Ability to deliver rapid, high-quality results within structured project timelines.

Preferred Skills:

- Experience with orchestration and transformation tools (e.g., Airflow, dbt, Azure Data Factory, or Python-driven pipeline movers).

- Familiarity with enterprise or industrial data integration platforms.

- Version control using Git.