Sr. Data Engineer

HARMAN India

3 - 8 years

20 - 25 Lacs

bengaluru

Posted:18 hours ago| Platform:

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Skills Required

data center design snowflake python rdbms dynamo db glue amazon redshift airflow big data technologies pyspark data warehousing data engineering sql server sql postgresql lambda expressions iam data warehousing concepts etl aws communication skills

Work Mode

Work from Office

Job Type

Full Time

Job Description

Bachelor s or Master s degree in Computer Science, Software Engineering, or a related field
5+ yrs
experience in data engineering roles
3+ years of experience in DWH/ETL Domain using AWS tech stack such as Redshift, S3, Glue, Lambda and IAM
Proficiency in PySpark/Python/SQL and designing data models and data standards
Deep understanding of ETL/ELT processes, data warehousing concepts, and big data technologies
Experience building & managing data pipelines using tools like Glue, Airflow, AWS Step Functions, or similar
Experience in RDMS & No-SQL databases: SQL Server databases, PostgreSQL, DynamoDB, or Aurora
Experience in dimensional modeling & schema design; Star and Snowflake modelProven ability to lead & mentor data engineers towards innovative and disciplined environment
Strong problem-solving skills, with a process/methodical approach to resolve technical challenges and risksExcellent analytical, verbal and communication skills for stakeholder and team management
Initiate/Incubate/execute PoCs to validate the use cases targeting enhanced ETL/DWH engineering solutions
Provide Architectural Guidance the team about data pipelines/ storage/ operations/ client delivery
Initiate and drive cost optimization programs leverage design & Infra enhancements
Implement best practices for data engineering, ETL, and DWH development in AWS cloud environmentConduct code reviews; Coach team members on coding practices and drive adherence to coding standards
Collaborate with cross-functional teams to finalize project requirements, timelines, and deliverables
Monitor project progress, identify risks, and ensure on-time delivery of data engineering projects
Optimize data models for performance and scalability; leverage latest AWS services to supplement scalable and configurable DWH architectures

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