– Technical Architect (AWS Data Engineering Lead)
1. Basic Information
- Job Title: Technical Architect (AWS Data Engineering Lead)
- Experience: 6 to 10 Years
- Shift Timing: 12 PM – 9 PM IST and/or 2 PM – 11 PM IST
2. Role Overview
We are looking for a hands-on AWS Technical Lead – Data Engineering with 6 to 10 years of experience to design and deliver scalable, secure, and high-performance data platforms on AWS
This role requires strong individual contribution with end-to-end technical ownership. The candidate will collaborate closely with global teams, architects, and clients to deliver enterprise-grade data engineering solutions
The ideal candidate should have deep expertise in AWS data services, SQL, and Python, along with the ability to design, build, and optimize reliable data pipelines for analytics and business use cases
3. Must-Have Skills
Cloud & Data Engineering (AWS)
- Strong hands-on experience with:
- Amazon S3, AWS Glue, Athena, Redshift
- Experience designing cloud-native data lakes and data warehouses
- Deep understanding of batch and streaming data pipelines
- Experience building scalable and fault-tolerant data workflows
SQL & Python (Mandatory)
- Strong expertise in SQL, including:
- Complex transformations and aggregations
- Performance tuning and analytics queries
- Experience working with large-scale datasets in Redshift/Athena
- Strong Python programming skills for data engineering use cases
PySpark / Spark Processing
- Hands-on experience with Spark / PySpark
- Build reusable ETL components and utilities
- Strong understanding of:
- Data modeling
- Transformations
- Performance optimization
Data Processing & Engineering
- Experience with distributed processing frameworks (Spark/PySpark)
- Handling structured, semi-structured, and unstructured data
- Expertise in:
- Schema design
- Partitioning
- Query optimization
DevOps & Platform Engineering
- Experience with Infrastructure as Code (Terraform / CloudFormation)
- Hands-on experience in building CI/CD pipelines for data platforms
- Exposure to containerization (Docker, ECS, EKS)
Collaboration & Ownership
- Strong ownership mindset for:
- Solution quality
- Performance
- Production stability
- Excellent communication and stakeholder collaboration skills
4. Good-to-Have Skills
- Experience with streaming technologies (Kinesis, Kafka, MSK)
- Exposure to Lakehouse architectures and modern data platforms
- Integration with BI and analytics tools
- Knowledge of:
- Data governance
- Data quality frameworks
- Metadata management
- Familiarity with FinOps (cost optimization on AWS)
- Exposure to Marketing/Customer Data Platforms (CDP / MarTech)
- Experience working in Agile delivery models with global teams
5. Key Responsibilities
Data Platform Design & Development
- Design and implement AWS-based data engineering solutions
- Build and optimize batch and streaming pipelines
- Develop:
- SQL-driven data transformations
- Python-based pipelines
- Design efficient data models for:
- Scalability
- Performance
- Cost optimization
Delivery & Quality Ownership
- Own data engineering deliverables from development to production support
- Perform:
- Performance tuning
- Cost optimization
- Capacity planning
- Troubleshoot complex data and production issues
- Ensure solutions meet security, reliability, and scalability standards
Collaboration & Client Engagement
- Work with architects, product owners, and stakeholders
- Translate business requirements into technical data solutions
- Provide:
- Technical estimates
- Implementation trade-offs
- Participate in solution design and architecture discussions
Engineering Best Practices
- Follow coding standards and data engineering best practices
- Participate in code reviews and continuous improvement initiatives
- Ensure compliance with AWS, security, and governance guidelines
6. Education Qualification
- Bachelor’s or Master’s degree in:
- Computer Science
- Information Systems
- Data Engineering
- or related field
7. Certifications
- Preferred:
- AWS Certified Data Analytics
- AWS Solutions Architect
( Any two preferred)
- Plus:
- Databricks
- Snowflake or other cloud data platform certifications