Weekday AI
LeadAWSDataEngineer
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“Lead AWS Data Engineer at Weekday AI. Skills: Data Engineering, Cloud Data Platforms, AWS Services, Data Pipelines. Design scalable data pipelines. Develop scalable data pipelines”
Industry & Context.
Problem-solving skills; Troubleshooting
What They're Looking For.
Must Have
8–10 years of experience in Data Engineering, Data Warehousing experience, Cloud Data Platform development experience, AWS expertise, Python proficiency, PySpark proficiency, SQL proficiency, PL/SQL proficiency, ETL/ELT pipelines experience, Data ingestion frameworks experience, Integration solutions experience, Data warehousing concepts knowledge, Dimensional modeling knowledge, Database architecture knowledge, Structured datasets experience, Semi-structured datasets experience, Unstructured datasets experience, Data Lake knowledge, Data Warehouse knowledge, Lakehouse environments knowledge, Workflow orchestration experience, Event-driven architectures experience, Distributed data processing systems experience, Data governance implementation, Data quality frameworks implementation, Security best practices implementation, Analytical thinking, Problem-solving skills, Attention to detail
Nice to Have
AI initiatives support experience, Machine Learning support experience, Data Science support experience, Advanced Analytics support experience, CI/CD pipelines exposure, DevOps practices exposure, Infrastructure as Code exposure, Agile delivery methodologies exposure
What You'll Do.
Design scalable data pipelines
Develop scalable data pipelines
Maintain scalable data pipelines
Design ETL/ELT processes
Develop ETL/ELT processes
Maintain ETL/ELT processes
Design data integration frameworks
Develop data integration frameworks
Maintain data integration frameworks
Build cloud-native data solutions
Develop large-scale data processing workflows
Optimize large-scale data processing workflows
Design enterprise data warehouses
Implement enterprise data warehouses
Design dimensional models
Implement dimensional models
Design reporting structures
Implement reporting structures
Collaborate with business stakeholders
Collaborate with product teams
Collaborate with analysts
Collaborate with data scientists
Deliver data-driven solutions
Ensure data governance
Ensure data compliance
Ensure data lifecycle management
Optimize database performance
Optimize query execution
Optimize high-volume data processing
Implement monitoring mechanisms
Implement logging mechanisms
Implement alerting mechanisms
Implement troubleshooting mechanisms
Participate in architecture reviews
Participate in cloud modernization
Participate in technical design
Support machine learning use cases
Support advanced analytics use cases
Drive continuous improvement
Mentor junior engineers
Promote engineering best practices
Promote code quality standards
Promote knowledge sharing
Support deployment activities
Resolve production issues
How You'll Work.
Team & Collaboration
Business stakeholders; Product teams; Analysts; Data scientists; Engineering teams
Communication Scope
Stakeholder management
Process & Methodology
Agile delivery methodologies
Full Job Description
**This role is for one of the Weekday's clients** **Salary range: Rs 1500000 - Rs 2500000 (ie INR 15-25 LPA)** Experience: 7+ yrs Location: Bengaluru, Pune Job Type: full-time We are looking for 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. **Requirements** ### 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. * Parti
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