Job descriptionJob Title: Senior AWS Lead Experience Level:
10–12 Years Location:
Hyderabad/Indore Job Type:
Full-time .
Position Summary We are seeking a highly experienced
AWS Data Engineering Lead
(10-12 years) to lead the design and delivery of enterprise-scale data platforms. This role requires a unique blend of deep technical expertise across AWS data services and strong functional knowledge of
SAP Data Models
(ECC, S/4HANA) alongside traditional and modern data sources like
MySQL, Oracle, REST/OData APIs, and RDS . You will be responsible for architecting end-to-end Data Lakehouse solutions that consolidate disparate data sources into a unified, high-performance analytics platform. Key Responsibilities Multi-Source Data Architecture:
Design and implement scalable AWS Data Lake and Lakehouse architectures that integrate SAP (ERP, BW) and non-SAP sources (MySQL, Oracle, RDS, On-premise). SAP Functional Integration:
Leverage deep functional understanding of SAP modules (FICO, SD, MM) and table structures (e.g., KNA1, MARA, BSEG) to design efficient extraction strategies using
SAP ODP, OData APIs, SLT, and BW extractors . Modern API Ingestion:
Architect and build ingestion frameworks for
RESTful and OData APIs
using AWS Glue, Lambda, and Amazon API Gateway. Enterprise ETL/ELT:
Lead the development of robust data pipelines using
AWS Glue (PySpark), Amazon EMR, and AWS Step Functions , ensuring optimized CDC (Change Data Capture) from RDS, Oracle, and MySQL sources. Data Modeling & Warehousing:
Define conceptual, logical, and physical data models for
Amazon Redshift
and S3-based storage using open table formats like
Apache Iceberg . Performance & Cost Engineering:
Optimize environments for large-scale data processing, focusing on query performance and cost-efficiency using AWS Lake Formation. Stakeholder Communication:
Act as the primary technical liaison between business functional owners, SAP consultants, and data engineering teams to translate business needs into technical specifications. Technical Requirements AWS Core:
Mastery of S3, Glue, Redshift, Lambda, Athena, Airflow, MWAA, EMR, Kinesis, Lake Formation, and RDS. SAP Specialization:
Proven experience with SAP S/4HANA or ECC data extraction; knowledge of SAP BTP or Datasphere is a significant plus. Database Expertise:
Strong hands-on experience with
MySQL, Oracle , and
AWS Aurora/RDS . API & Integration:
Proficiency in consuming and architecting
REST APIs
and
OData
services for data ingestion. Languages:
Expert-level
Python/PySpark
and
Advanced SQL . Preferred Qualifications 10-12 years of IT experience, with 5+ years specifically in AWS Data Architecture. AWS Certified Data Engineer – Associate or AWS Certified Solutions Architect – Professional. Excellent verbal and written communication for high-level stakeholder management. Experience in Agile/DevOps methodologies for data engineering.