DescriptionThis role is for one of the Weekday's clients
Salary range: Rs 1500000 - Rs 3300000 (ie INR 15-33 LPA)
Min Experience: 5 years
Location: Bangalore
JobType: full-time
We are seeking a highly skilled and experienced Senior Data Engineer to design, build, and maintain scalable data pipelines that support growing data demands and complexity. This role will work closely with cross-functional teams to optimize data models, enhance data accessibility, and empower data-driven decision-making across the organization.
RequirementsKey Responsibilities:
1. Data Pipeline Development & Maintenance:
- Architect, develop, and manage robust data pipelines and ETL processes in a cloud-native environment to support analytics and machine learning workloads.
- Leverage AWS services such as RDS, Glue, Lambda, and S3 to manage and transform large-scale datasets.
2. DevOps & Automation:
- Apply DevOps best practices to data engineering processes, focusing on automation, CI/CD, and repeatable infrastructure setup.
- Develop Infrastructure as Code (IaC) templates using tools like Terraform or CloudFormation to provision and manage AWS data resources.
- Build reliable monitoring, logging, and alerting systems to maintain high performance and data quality across pipelines and models.
Qualifications:
- Minimum 5+ years of hands-on experience in ETL development and data engineering roles.
Required Skills and Competencies:
- Cloud Platforms: Strong hands-on experience with AWS services such as S3, Glue, Lambda, and SageMaker.
- Programming: Advanced Python skills, including use of data processing libraries like Pandas.
- DevOps Practices: Familiarity with CI/CD workflows, infrastructure automation using Terraform/CloudFormation, and system monitoring via CloudWatch or similar tools.
- Data Engineering Fundamentals: Solid understanding of data warehousing, data lakes, and ETL/ELT strategies.
- Collaboration: Excellent communication skills and experience working within cross-functional Agile teams.
- Analytical Thinking: Strong problem-solving capabilities and the ability to analyze complex data workflows.
- Organizational Skills: Effective time management, planning, and the ability to meet tight deadlines.
- Listening & Interpretation: Ability to understand business requirements and translate them into technical solutions.
Key Skills:
ETL, AWS (S3, Lambda, Glue, RDS, SageMaker), Python, Terraform, CloudFormation, CI/CD, Data Pipelines, DevOps, CloudWatch