Data Engineering Lead

USEReady Technology Private Limited; Bengaluru; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

USEReady Technology Private Limited in Bengaluru seeks an experienced Data Engineering Lead to drive end-to-end ELT pipelines. You will migrate data from SQL sources into Snowflake and orchestrate bulk file transfers into Azure Data Lake Storage, shaping scalable data integration for enterprise analytics.

You will design, build, and maintain pipelines, write high-performance SQL, perform data reconciliation, and collaborate with client teams to ensure governance and security alignment.

Qualifications

• Experience in designing, building, and optimizing production ELT/ETL pipelines.
• Strong SQL skills including performance tuning for large datasets.
• Hands-on Snowflake data loading and modeling experience.
• Solid experience with Azure Data Lake Storage Gen2 and file transfer patterns.

Responsibilities

• Design, build, and maintain scalable ELT/ETL pipelines and data workflows for ingestion and transformation.
• Execute structured data extraction and landing from SQL databases into Snowflake staging and core layers.
• Build, execute, and monitor file movement tasks to transfer data into ADLS.
• Write and optimize high-performance SQL queries for data modeling, validation, and staging transformations.
• Conduct data reconciliation and completeness checks to ensure zero loss across pipelines.
• Collaborate with the Lead Data Integration Expert and client teams to align with governance and security protocols.

Skills

ELT pipelines

SQL

Snowflake

Azure Data Lake Storage

File processing

Agile execution

Tools

Airflow

dbt

Azure Data Factory

Python

Git

SAP

Job description

USEReady is a global analytics and data management solutions company that helps enterprises harness the power of data to drive smarter decisions. With a strong presence across North America, USEReady partners with Fortune 500 companies to deliver end-to-end analytics, BI, data engineering, and AI/ML solutions. Our Bangalore office serves as a key hub for our finance, technology, and delivery operations.

Description

Primary Focus: SQL-to-Snowflake Data Transfer, ELT Pipelines & File-to-ADLS Ingestion

Role Overview

We are seeking an experienced Data Engineering Lead 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 and SAP.

• Version control using Git.