Data Engineer ( Snowflake and ADLS)

Useready; Bengaluru; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

Useready in Bengaluru seeks an experienced Data Engineer to design and execute end-to-end ELT pipelines, migrating data from SQL sources into Snowflake and orchestrating file transfers into ADLS.

You will build scalable pipelines, write high-performance SQL, and collaborate with client teams to ensure governance and security within Agile timelines.

Qualifications

• Hands-on experience building production ELT/ETL pipelines and data workflows.
• Strong SQL expertise with large datasets and performance tuning.
• Experience loading and modeling data in Snowflake with staging strategies.
• Work with Azure Data Lake Storage (ADLS Gen2) and file transfer patterns.
• Experience handling bulk file formats (CSV, Parquet, JSON).
• Ability to deliver quickly within structured project timelines.

Responsibilities

• Design, build, and maintain scalable ELT/ETL pipelines for ingestion and transformation.
• Execute data extraction and landing from SQL databases into Snowflake layers.
• Create and monitor file movement tasks to ADLS for bulk transfers.
• Write and optimize high-performance SQL queries for staging transformations.
• Perform data reconciliation to ensure zero data loss during migration.
• Collaborate with Lead Data Integration Expert and client teams on governance.

Skills

ELT / Data Pipelines

SQL & Relational Databases

Snowflake

Azure Cloud Storage

File Processing

Agile Execution

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.


• Version control using Git.