Hands-on AWS Technical Lead to design, build, and operate scalable data platforms and pipelines on AWS. Responsible for SQL- and Python-based ETL, Spark/PySpark processing, data modeling, performance tuning, IaC, CI/CD, containerization, production support, and collaborating with global teams and stakeholders to deliver secure, cost-optimized data solutions.
Job Description:
Job Description – 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
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 SkillsCloud & 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
- 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
- Hands-on experience with Spark / PySpark
- Build reusable ETL components and utilities
- Strong understanding of:
- Data modeling
- Transformations
- Performance optimization
- Experience with distributed processing frameworks (Spark/PySpark)
- Handling structured, semi-structured, and unstructured data
- Expertise in:
- Schema design
- Partitioning
- Query optimization
- Experience with Infrastructure as Code (Terraform / CloudFormation)
- Hands-on experience in building CI/CD pipelines for data platforms
- Exposure to containerization (Docker, ECS, EKS)
- Strong ownership mindset for:
- Solution quality
- Performance
- Production stability
- Excellent communication and stakeholder collaboration 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
- 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
- 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
- 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
- Follow coding standards and data engineering best practices
- Participate in code reviews and continuous improvement initiatives
- Ensure compliance with AWS, security, and governance guidelines
- Bachelor’s or Master’s degree in:
- Computer Science
- Information Systems
- Data Engineering
- or related field
- Preferred:
- AWS Certified Data Analytics
- AWS Solutions Architect
(Any two preferred)
- Plus:
- Databricks
- Snowflake or other cloud data platform certifications
Location:
DGS India - Mumbai - Goregaon Prism TowerBrand:
MerkleTime Type:
Full timeContract Type:
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