Lead AWS Data Developer

Weekday AI

Job Overview

Location

Bengaluru, Karnataka, India

Salary

INR 1,500,000 - 2,500,000 monthly

Employment Type

Full-time

Work Arrangement

On-site

Sector

Information Technology & Software

Experience Level

Senior (5-8 years)

Application Deadline

June 20, 2026

About the Company

Weekday AI is a rapidly growing company backed by Y Combinator, recognized as a Product Hunt #1 product of the day. They are at the forefront of revolutionizing the hiring landscape by building the largest database of white-collar talent in India. Weekday AI leverages advanced outreach tools to achieve exceptional response rates, aiming to redefine recruitment processes. Their mission is to innovate within the hiring industry, utilizing technology to connect talent with opportunities more effectively. The company fosters an environment of rapid development and impactful solutions, driven by a commitment to excellence and cutting-edge technology.

Job Description

We are seeking a highly experienced Senior Data Engineer to design, build, and optimize scalable cloud-based data platforms that power enterprise analytics, reporting, and AI-driven initiatives. This role is ideal for a hands-on data engineering professional who combines deep technical expertise with strong business understanding to create reliable, secure, and high-performance data solutions.

You will be responsible for developing modern data architectures, building robust ETL/ELT frameworks, and leveraging cloud-native technologies to support large-scale data processing and analytics. Working closely with business stakeholders, data scientists, analysts, and engineering teams, you will transform complex business requirements into scalable technical solutions while driving best practices in data engineering, governance, performance optimization, and platform reliability.

Required Skills

AWSData EngineeringETLELTPythonPySparkSQLPL/SQLData WarehousingData PipelinesCloud Data PlatformsRedshiftGlueLambdaAuroraOpenSearchStep FunctionsSNSS3Dimensional ModelingDatabase ArchitectureData GovernanceData QualityData SecurityAgile MethodologiesCI/CDDevOpsInfrastructure as Code (IaC)

Key Responsibilities

Design, develop, and maintain scalable data pipelines, ETL/ELT processes, and data integration frameworks.
Build cloud-native data solutions using AWS services such as Glue, Lambda, Redshift, Aurora, OpenSearch, Step Functions, SNS, and S3.
Develop and optimize large-scale data processing workflows using Python, PySpark, SQL, and PL/SQL.
Design and implement enterprise data warehouses, data marts, dimensional models, and reporting structures.
Collaborate with business stakeholders, product teams, analysts, and data scientists to deliver data-driven solutions.
Ensure data quality, governance, security, compliance, and lifecycle management across the data ecosystem.
Optimize database performance, query execution, and high-volume data processing workloads.
Implement monitoring, logging, alerting, and troubleshooting mechanisms to maintain platform reliability.
Participate in architecture reviews, cloud modernization initiatives, and technical design discussions.
Support AI, machine learning, and advanced analytics use cases through scalable data infrastructure.
Drive continuous improvement initiatives focused on performance, scalability, and operational excellence.
Mentor junior engineers and promote engineering best practices, code quality standards, and knowledge sharing.
Support deployment activities, production issue resolution, and ongoing platform enhancements.

Qualifications

8–10 years of experience in Data Engineering, Data Warehousing, and Cloud Data Platform development.
Strong expertise in AWS cloud services, including Glue, Lambda, Redshift, Aurora, OpenSearch, Step Functions, SNS, and S3.
Advanced proficiency in Python and PySpark for large-scale data processing and transformation.
Strong command of SQL and PL/SQL development and optimization.
Extensive experience building ETL/ELT pipelines, data ingestion frameworks, and integration solutions.
Deep understanding of data warehousing concepts, dimensional modeling, and database architecture.
Experience working with structured, semi-structured, and unstructured datasets.
Strong knowledge of modern data architectures, including Data Lakes, Data Warehouses, and Lakehouse environments.
Familiarity with workflow orchestration, event-driven architectures, and distributed data processing systems.
Experience implementing data governance, quality frameworks, and security best practices.
Strong analytical thinking, problem-solving skills, and attention to detail.
Excellent communication and stakeholder management abilities.
Experience supporting AI, Machine Learning, Data Science, or Advanced Analytics initiatives is highly desirable.
Exposure to CI/CD pipelines, DevOps practices, Infrastructure as Code (IaC), and Agile delivery methodologies is a plus.
AWS certifications or equivalent cloud credentials are highly valued.
A proactive, ownership-driven mindset with a passion for building scalable and reliable data platforms.

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 sophisticated analytics and AI solutions. This role is pivotal in shaping the future of data infrastructure, focusing on designing, building, and optimizing scalable cloud-based data platforms. You will leverage critical technologies such as AWS Glue, Redshift, PySpark, and Data Warehousing to enhance business intelligence and drive data-driven decision-making. Your impact will be measured by the efficiency and reliability of data systems, directly contributing to improved business ROI and strategic growth initiatives.