4 days ago
Hyderābād, IndiaMid Level
Responsibilities
- Architect and implement scalable, reliable, secure data pipelines and infrastructure for analytics, reporting, and business operations.
- Unify fragmented data pipelines and build robust, reusable data models and data integration services.
- Define and enforce data modeling, data lineage, governance, consistency, reusability, and quality standards.
- Build data platforms and frameworks supporting batch and real-time processing at scale.
- Lead design and code reviews and promote best practices in data development, documentation, testing, and monitoring.
- Implement secure and compliant data solutions that meet internal and external regulatory requirements, including GDPR.
- Evaluate emerging technologies to improve platform performance, cost efficiency, and scalability.
- Collaborate with software engineers, product managers, analytics teams, and business stakeholders to define data requirements and solution architectures.
- Mentor junior engineers and contribute to team hiring and onboarding.
Requirements
- At least 3 years of data engineering experience.
- Experience with data modeling, data warehousing, and building ETL pipelines.
- Experience with SQL.
- Preferred experience with AWS technologies including Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions.
- Preferred experience with non-relational databases and data stores, including object storage, document or key-value stores, graph databases, and column-family databases.
About Amazon
Amazon builds and operates a global e-commerce marketplace, logistics network, and consumer devices, and provides cloud computing via AWS for businesses and developers. The company earns revenue from online retail, third‑party seller services, subscriptions like Prime, advertising, and AWS usage. Founded in 1994 and headquartered in Seattle, it is publicly traded on NASDAQ (AMZN) and serves customers in dozens of countries.