Lead Data Engineer at Weekday AI

Coimbatore, tamil nadu, India -

Full Time

Start Date

Immediate

Expiry Date

08 Sep, 26

Salary

2500000.0

Posted On

10 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Java, Google Cloud Platform, BigQuery, Dataflow, SQL, ETL/ELT Pipelines, Data Modeling, Data Warehousing, Distributed Data Processing, Data Governance, Workflow Orchestration, Backend Development, Cloud-native Engineering, Data Architecture, Data Quality Frameworks

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Salary range: Rs 1200000 - Rs 2500000 (ie INR 12-25 LPA) Experience: 7+ yrs Location: Pune, Bangalore, Chennai, Coimbatore Job Type: full-time We are looking for a skilled Data Engineer who is passionate about building scalable data platforms and enabling data-driven decision-making. This role involves designing, developing, and maintaining robust data pipelines, processing large-scale datasets, and ensuring the availability, reliability, and performance of data systems. The ideal candidate will have strong expertise in cloud-based data engineering, backend development, and modern data processing technologies. You will work closely with cross-functional teams to create efficient data solutions that support analytics, reporting, machine learning, and business intelligence initiatives. Key Responsibilities Design, develop, and maintain scalable data pipelines for processing structured and unstructured data. Build and optimize cloud-based data solutions using modern data engineering best practices. Develop and manage data ingestion, transformation, validation, and orchestration workflows. Create reliable ETL/ELT pipelines to support analytics, reporting, and operational use cases. Work with large datasets to ensure data quality, consistency, and accessibility across systems. Develop and optimize backend services and data processing applications using Java. Implement data governance, monitoring, and performance optimization practices. Collaborate with product, analytics, and engineering teams to understand data requirements and deliver scalable solutions. Troubleshoot data pipeline issues and proactively identify opportunities for improvement. Ensure high availability, security, and scalability of data infrastructure. Participate in architecture discussions and contribute to data platform modernization initiatives. Support business intelligence, advanced analytics, and machine learning teams with reliable data assets. What Makes You a Great Fit Strong experience in Data Engineering and building scalable data processing systems. Proficiency in Java and cloud-native data engineering practices. Hands-on experience with Google Cloud Platform (GCP) and its data ecosystem. Strong understanding of data warehousing, data modeling, and distributed data processing concepts. Experience building and maintaining high-performance ETL/ELT pipelines. Familiarity with BigQuery, Dataflow, and other cloud-based data processing technologies is highly desirable. Strong SQL skills and experience working with large-scale datasets. Understanding of data architecture, data governance, and data quality frameworks. Experience with workflow orchestration, monitoring, and automation tools. Strong analytical thinking and problem-solving abilities. Ability to collaborate effectively with cross-functional stakeholders and communicate technical concepts clearly. Self-driven mindset with a focus on ownership, scalability, and continuous improvement.

Responsibilities

Design, develop, and maintain scalable data pipelines and cloud-based solutions for processing structured and unstructured data. Collaborate with cross-functional teams to support analytics, reporting, and machine learning initiatives through robust data infrastructure.