Key skills
Amazon RedshiftAWSAzureBigQueryCloudETLGoogle Cloud PlatformHadoopJavaKafkaMicroservicesNoSQLPythonScalaSparkSQLData EngineeringData WarehousingSnowflakeRedshiftGCPGoogle CloudGitVersion ControlPerformance Optimization
About this role
Role Overview
- Design, build, and maintain scalable data pipelines and ETL processes
- Develop and optimize data architectures and data models
- Work with large datasets across structured and unstructured sources
- Ensure data quality, integrity, and performance optimization
- Collaborate with Data Scientists, Analysts, and cross-functional teams
- Implement data security and governance standards
- Monitor and troubleshoot production data issues
- Participate in code reviews and best practices implementation
Requirements
- 10+ years of experience in Data Engineering
- Strong programming skills in Python / Java / Scala
- Hands-on experience with ETL tools and data pipeline frameworks
- Strong experience with SQL & NoSQL databases
- Expertise in data warehousing solutions (Snowflake, Redshift, BigQuery, etc.)
- Experience with big data technologies (Spark, Hadoop, Kafka)
- Good understanding of REST APIs & Microservices architecture
- Experience with Git/version control systems
- Exposure to cloud platforms (AWS / Azure / GCP)
Tech Stack
- Amazon Redshift
- AWS
- Azure
- BigQuery
- Cloud
- ETL
- Google Cloud Platform
- Hadoop
- Java
- Kafka
- Microservices
- NoSQL
- Python
- Scala
- Spark
- SQL
Benefits
- Immediate joiners preferred
- Mandatory Requirements LinkedIn Profile (Mandatory for submission)
- Willingness to work in US Shift (EST overlap required)
- Below documents are mandatory: ID Proofs Educational Documents Previous Employment Documents