7 months ago
Noida, IndiaSenior
Responsibilities
- Design and develop backend services, data APIs, and serverless components supporting analytics and application workloads.
- Build and operate event-driven architectures using S3, EventBridge, SNS/SQS, Lambda, Step Functions, and AWS Glue for batch and near-real-time ETL workloads.
- Implement AWS Glue jobs, workflows, and crawlers to load, transform, and curate data in Amazon Redshift and the broader data warehouse.
- Model, optimize, and manage star/snowflake schemas, partitioning, distribution keys, and sort keys for performant SQL and BI queries.
- Enable Amazon QuickSight reporting and authoring through data preparation, semantic modeling, row-level security, and dashboard performance tuning.
- Apply scalable big data storage and compute practices, including S3 data lakes, Parquet, pushdown, and partition pruning.
- Design monitoring, logging, and alerting for serverless and event-driven workloads using CloudWatch, X-Ray, and related services.
- Collaborate with data engineers, data scientists, and product teams to translate business and AI/analytics requirements into technical solutions.
- Contribute to architecture decisions, design reviews, AWS best-practice adoption, security, IAM, networking, cost optimization, and reliability.
- Mentor engineers in serverless, data, AI application patterns, coding standards, and cloud-native design.
Requirements
- 4–6 years of hands-on experience building AWS applications and services, ideally as a cloud application architect or backend engineer.
- Advanced proficiency in Python for backend development, ETL, and automation, including AWS Lambda and AWS Glue jobs.
- Experience with AWS serverless computing, including Lambda, API Gateway, Step Functions, and event-driven integration patterns.
- Experience designing and maintaining ETL pipelines and data workflows using AWS Glue and related data integration tooling.
- Strong SQL skills and experience with analytical databases and data warehouses, especially Amazon Redshift.
- Knowledge of dimensional modeling, fact and dimension design, slowly changing dimensions, data partitioning, and indexing.
- Experience with AWS big data workloads, including S3 data lakes, Parquet or ORC, Redshift Spectrum, Athena, or similar technologies.
- Hands-on experience with BI and data visualization tools, preferably Amazon QuickSight, including dataset design, dashboards, and security.
- Understanding of AWS cloud infrastructure fundamentals, including VPCs, subnets, networking, IAM, encryption, and security best practices.
- At least one relevant AWS certification, such as Solutions Architect, Data Analytics, or Developer, or equivalent practical expertise.
Benefits
- Flexible working arrangements are considered wherever possible, and the company has been recognized as a remote-friendly employer.
- Benefits may include health coverage, wellbeing and support programs, retirement, vacation and sick leave, maternity, paternity and adoption leave, continuing education and training, and voluntary benefits.
- Virtual interviews must be conducted on video.
- Employment is contingent on successfully completing a background check consistent with company policy.
