Weekday AI
LeadAWSDataDeveloper
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“Lead AWS Data Developer at Weekday AI. Skills: Data Engineering, Cloud Data Platforms, AWS Services, Data Pipelines. Design data pipelines. Develop data pipelines”
Industry & Context.
Analytical thinking; Problem-solving skills
What They're Looking For.
Must Have
7+ years of experience, 8–10 years of experience in Data Engineering, Expertise in AWS cloud services, Advanced proficiency in Python, Advanced proficiency in PySpark, Command of SQL, Command of PL/SQL development, Extensive experience building ETL/ELT pipelines, Deep understanding of data warehousing concepts, Deep understanding of dimensional modeling, Deep understanding of database architecture, Experience working with structured datasets, Experience working with semi-structured datasets, Experience working with unstructured datasets, Knowledge of modern data architectures, Familiarity with workflow orchestration, Familiarity with event-driven architectures, Familiarity with distributed data processing systems, Experience implementing data governance, Experience implementing data quality frameworks, Experience implementing security best practices, Analytical thinking, Problem-solving skills, Attention to detail, Excellent communication abilities, Excellent stakeholder management abilities
Nice to Have
Experience supporting AI initiatives, Experience supporting Machine Learning initiatives, Experience supporting Data Science initiatives, Experience supporting Advanced Analytics initiatives, Exposure to CI/CD pipelines, Exposure to DevOps practices, Exposure to Infrastructure as Code (IaC), Exposure to Agile delivery methodologies, AWS certifications, Cloud credentials
What You'll Do.
Design data pipelines
Develop data pipelines
Maintain data pipelines
Develop ETL processes
Maintain ETL processes
Design data integration frameworks
Develop data integration frameworks
Maintain data integration frameworks
Build cloud-native data solutions
Develop data processing workflows
Optimize data processing workflows
Design enterprise data warehouses
Design dimensional models
Design 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 initiatives
Participate in technical design discussions
Support machine learning use cases
Support advanced analytics use cases
Drive continuous improvement initiatives
Mentor junior engineers
Promote engineering best practices
Promote code quality standards
Promote knowledge sharing
Support deployment activities
Support production issue resolution
Support ongoing platform enhancements
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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