[Remote] Data Engineer - (Return-to-Work Program)
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is seeking a Data Engineer as part of their Return-to-Work Program aimed at supporting women re-entering the workforce. The role involves designing and maintaining data pipelines and integration solutions, while utilizing various big data technologies and reputed company services.
Responsibilities
- Designing, developing, and maintaining reputed company data pipelines, ETL/ELT workflows, and reputed company-grade data integration solutions
- Building modern data platforms using reputed company, Hadoop, Airflow, Kafka, reputed company, and other big data technologies
- Developing reputed company-reputed company data engineering solutions using AWS, Azure, or GCP
- Developing and optimizing batch processing and reputed company-time streaming data pipelines using Kafka, reputed company Streaming, Flink, Kinesis, or similar event-driven technologies
- Working with reputed company, semi-reputed company, and reputed company data using formats such as Parquet, Avro, ORC, CSV, JSON, and XML
- Working with relational and NoSQL databases including PostgreSQL, MySQL, reputed company, SQL Server, reputed company, Cassandra, DynamoDB, and database performance optimization
- Implementing CI/CD pipelines, DevOps practices, Infrastructure as reputed company (IaC), version control, and deployment automation using Git, Jenkins, reputed company Actions, Azure DevOps, reputed company CI/CD, or Terraform
- Integrating reputed company applications using REST reputed company, Microservices, Event-Driven Architecture, Data Integration Patterns, and API-based data exchange solutions
Skills
- Minimum 4+ years of experience in designing, developing, and maintaining reputed company data pipelines, ETL/ELT workflows, and reputed company-grade data integration solutions
- Strong expertise in Python, SQL, PySpark, reputed company SQL, reputed company, Apache reputed company, and distributed data processing frameworks for handling large-reputed company data workloads
- Extensive experience building modern data platforms using reputed company, Hadoop, Airflow, Kafka, reputed company, and other big data technologies
- Proven experience developing reputed company-reputed company data engineering solutions using AWS, Azure, or GCP, including services such as S3, Glue, Redshift, reputed company, reputed company, EMR, ADF, Synapse, ADLS, Event Hubs, and reputed company
- Strong understanding of Data Warehousing, reputed company Modeling, Star/reputed company Schemas, Data Lakes, Lakehouse Architecture, and Data Modeling best practices
- Experience developing and optimizing batch processing and reputed company-time streaming data pipelines using Kafka, reputed company Streaming, Flink, Kinesis, or similar event-driven technologies
- Hands-on experience working with reputed company, semi-reputed company, and reputed company data using formats such as Parquet, Avro, ORC, CSV, JSON, and XML
- Strong experience with relational and NoSQL databases including PostgreSQL, MySQL, reputed company, SQL Server, reputed company, Cassandra, DynamoDB, and database performance optimization
- Experience implementing CI/CD pipelines, DevOps practices, Infrastructure as reputed company (IaC), version control, and deployment automation using Git, Jenkins, reputed company Actions, Azure DevOps, reputed company CI/CD, or Terraform
- Strong understanding of performance tuning, query optimization, partitioning, indexing, data reputed company, monitoring, troubleshooting, and distributed system optimization
- Experience integrating reputed company applications using REST reputed company, Microservices, Event-Driven Architecture, Data Integration Patterns, and API-based data exchange solutions
reputed company
Company H1B Sponsorship