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Senior Data Engineer at Weekday AI. This role is for one of the Weekday's clients. Min Experience: 7 years. JobType: full-time. Key Responsibilities. . Design, develop, and maintain scalable, high-performance data pipelines using AWS technologies. . . Build and orchestrate ETL workflows leveraging . AWS Glue. , . Lambda. , . Step Functions. , and other services. . . Work with both structured and unstructured data to transform raw inputs into clean, analytics-ready datasets. . . Implement data lake and data warehouse architectures utilizing . AWS S3. , . Redshift. , . Athena. , and related tools. . . Collaborate with cross-functional teams to gather data requirements and ensure consistency, accuracy, and reliability. . . Optimize performance of large-scale data systems, SQL queries, and data workflows. . . Uphold data governance, privacy, and compliance standards within the AWS environment. . . 🌐 . Required Skills & Qualifications. . . . 7+ years. of experience in data engineering or similar roles. . . Deep expertise in AWS ecosystem including: . . . S3. , . Glue. , . Lambda. , . Redshift. , . Athena. , . EMR. , . Kinesis. , . IAM. , . Step Functions. . . . . Proficient in . Python. and . SQL. for data processing and transformation. . . Solid foundation in . data modeling. , . data warehousing. , and . big data processing. . . . Hands-on experience with orchestration tools like . Apache Airflow. or . AWS Step Functions. . . . Familiarity with . CI/CD pipelines. , . DevOps practices. , and version control systems like . Git. . . . Experience working in Agile development environments. . . ✅ . Preferred Skills. . . Experience with . Spark. or . PySpark. for large-scale data processing. . . Understanding of . data lakehouse. architectures and best practices. . . Exposure to cloud platforms such as . GCP. or . Azure. (nice to have). . . Strong problem-solving skills and the ability to clearly communicate complex data concepts. . . Key Skills. . AWS . . SQL . . Python . . ETL. . Company Location: India.