Data Engineer- Snowflake & Python

USEReady Inc.; Mohali, Gurugram District, Bengaluru; Hybrid; INR 900,000 - 1,400,000; Full time

Job summary

USEReady Inc. seeks an experienced Data Engineer to design and execute end-to-end ELT pipelines, migrating structured data from SQL sources into Snowflake and coordinating bulk file transfers into Azure Data Lake Storage.

You will build scalable data workflows, optimize SQL performance, and ensure data quality while collaborating with client teams on connectivity, security, and governance protocols.

Qualifications

• Proven experience building, optimizing, and monitoring production ELT/ETL pipelines.
• Strong SQL skills for large datasets across relational engines.
• Hands-on Snowflake loading, staging, COPY commands, bulk loading utilities.
• Experience with ADLS Gen2/Blob Storage and file transfer patterns.
• Experience with bulk file ingestion formats (CSV, Parquet, JSON).
• Ability to deliver within structured project timelines.

Responsibilities

• Design, build, and maintain scalable ELT/ETL pipelines for ingestion and transformation.
• Execute data extraction and landing from SQL sources into Snowflake staging and core layers.
• Coordinate file movement to Azure Data Lake Storage (ADLS) for bulk transfers.
• Write and optimize high-performance SQL queries for data modeling and validation.
• Perform data reconciliation to ensure zero loss across pipelines during migration.
• Collaborate with Lead Data Integration Expert and client teams on security and governance.

Skills

ELT pipelines

SQL & RDBMS

Snowflake

Azure ADLS

File processing

Agile execution

Tools

Snowflake

Azure Data Factory

Airflow

dbt

Python

Git

SAP

Job description

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: 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 and SAP.
• Version control using Git.