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 workflowsmigrating 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: Solid 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.

📌 Data Engineer Snowflake And Adls Bengaluru
🏢 USEReady
📍 Bengaluru