Lead Azure Data Engineer

Weekday AI

Job Overview

Location

Remote

Salary

INR 500,000 - 2,000,000 monthly

Employment Type

Full-time

Work Arrangement

Remote

Sector

Information Technology & Software

Experience Level

Senior (5-8 years)

Application Deadline

July 5, 2026

About the Company

Weekday AI, a Y Combinator-backed company and Product Hunt #1 product of the day, is at the forefront of revolutionizing the hiring landscape. They have established the largest database of white-collar talent in India and developed sophisticated outreach tools that achieve exceptional response rates. Their mission is to build the next frontier in hiring, leveraging technology to connect top talent with leading opportunities. By focusing on data-driven insights and advanced outreach strategies, Weekday AI aims to streamline the recruitment process for both employers and candidates, ensuring a more efficient and effective experience for all involved.

Job Description

You will leverage cutting-edge technologies such as Azure Data Factory, Databricks, and Spark to develop robust ETL/ELT pipelines, data lakes, and warehouse solutions. Your expertise will directly impact business intelligence, enabling data-driven decision-making and driving significant ROI through scalable, high-quality data architectures.

To apply for this role, click the Apply button on this page and follow the instructions.

Required Skills

Azure Data FactoryDatabricksAzure Synapse AnalyticsSparkPySparkSQLETLData LakesDelta LakeData WarehousingCloud ComputingDevOpsCI/CD

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines for processing large volumes of structured and unstructured data.
Build and manage cloud-based data platforms, including data lakes, data warehouses, and analytics solutions.
Develop and optimize data pipelines using Spark, PySpark, and cloud-native data services.
Work with real-time and batch data processing frameworks to ensure reliable and efficient data delivery.
Design robust data models and implement best practices for data quality, governance, and performance.
Optimize SQL queries, database performance, and large-scale analytics workloads.
Develop and maintain reporting and visualization solutions to support business stakeholders.
Collaborate with business, engineering, analytics, and product teams to define data requirements and solutions.
Support CI/CD processes, automation, monitoring, and deployment of data engineering solutions.
Create technical documentation and ensure adherence to modern engineering and data management standards.

Qualifications

7+ years of experience in Data Engineering, ETL development, and cloud-based analytics solutions.
Strong expertise in Azure Data Factory, Databricks, Azure Synapse Analytics, Spark, and PySpark.
Hands-on experience with data lakes, Delta Lake architecture, and modern big data technologies.
Strong SQL development, query optimization, and performance tuning skills.
Experience designing scalable cloud-hosted data platforms and enterprise-grade data architectures.
Knowledge of reporting and analytics tools, including data modeling and dashboard development.
Familiarity with CI/CD pipelines, DevOps practices, and cloud security concepts such as RBAC.
Strong problem-solving, communication, and stakeholder management skills.
Ability to translate business requirements into scalable technical data solutions while maintaining high standards of quality and reliability.

How to Apply

To apply for this role, click the Apply button on this page and follow the instructions.

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The Indian data engineering sector is experiencing rapid expansion, driven by increasing demand for cloud-based analytics and AI solutions. This role is pivotal in shaping the future of data infrastructure, focusing on designing, building, and optimizing sophisticated cloud-based data platforms. You will leverage cutting-edge technologies such as Azure Data Factory, Databricks, and Spark to develop robust ETL/ELT pipelines, data lakes, and warehouse solutions. Your expertise will directly impact business intelligence, enabling data-driven decision-making and driving significant ROI through scalable, high-quality data architectures.