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Job Description
Structured overview of role & requirementsAbout This Role
Plan, design, develop, and maintain AWS cloud-based data models, data pipelines, and standards for Data Integration, Data Lake, and Data Warehouse projects.
Develop, optimize, and troubleshoot ETL/ELT pipelines and data transformations (SQL, Python, PySpark) ensuring reliability, scalability, and compliance with governance standards.
Collaborate in migration of legacy pipelines, participate in solution design, maintain documentation, and support end-to-end data architecture including medallion data architecture.
Minimum Requirements
Minimum 3 years of experience as a Data Engineer.
Must have experience with cloud-based data platforms, especially AWS services including Redshift, Glue, Athena, Lambda, S3, Lake Formation, IAM, SQS, and Snowflake.
Proficient in SQL, Python scripting (Pandas/PySpark), and data modeling concepts including ELT, stored procedures, and data warehouse architecture.
Role based in Gurugram, India with hybrid work model; experience integrating CRM, ERP, marketing data sources into data lakes/warehouses.
Ideal Candidate Profile
Demonstrated ability to complete complex technical data engineering projects end-to-end with high-level design and architecture skills.
Experience working with AWS cloud-native data services and implementing advanced features like resource monitors, RBAC, query tuning, lake-house patterns, and data sharing.
Strong operational focus on maintaining production data pipelines with troubleshooting, performance optimization, and adherence to data security and governance.