Sequoia Connect
Posted 55 days agoVerified live 2d ago
Junior Data Engineer
Brief overview
Remote
UndergradOr in progress
Sponsors visasStated in posting
PythonSQLPySparkAWS S3AWS SNSAWS SQSAWS EMRAWS GlueAWS LambdaAWS RedshiftAWS Step FunctionsETL conceptsData processing fundamentalsGitLabTerraformSoftware Development Life Cycle (SDLC)
About the company
Sequoia Connectsequoia-connect.com
Sequoia Connect specializes in AI advisory and offers talent recruiting services for various technology specialists and IT consulting.
Job description
Summary
Sequoia Connect is a Talent-First Technology Ecosystem that connects elite professionals with the global digital landscape. They are currently seeking a Junior Data Engineer to assist in building and maintaining ETL pipelines, support workflow development, and collaborate with teams to meet data engineering needs.
Responsibilities
- Assist in building and maintaining ETL pipelines using Python and PySpark
- Support the development of workflows utilizing AWS Glue, Lambda, and Step Functions
- Work extensively with cloud data storage platforms, including S3, Redshift, RDS, and Oracle
- Write complex SQL queries for data extraction, transformation, validation, and reporting
- Help implement basic monitoring, logging, and error handling for data pipelines
- Support the ingestion and processing of data from APIs and JSON payloads
- Collaborate with software engineers, data analysts, and business stakeholders to understand requirements
- Contribute to code management, technical documentation, and deployment support activities
Skills
- Degree holders for the visa application process
- 0 to 4 years of software development or data engineering experience across relevant cloud platforms
- Good knowledge of Python and SQL
- Solid understanding of AWS services, specifically S3, SNS/SQS, EMR, Glue, Lambda, Redshift, and Step Functions
- Strong grasp of ETL concepts and data processing fundamentals
- Familiarity with GitLab, Terraform, and the Software Development Life Cycle (SDLC) from development to production
- Familiarity with PySpark, AWS managed services, data engineering best practices, and code optimization
- High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery
- Technologist DNA: A deep understanding of the difference between 'coding' and 'engineering.'
- Good analytical, problem-solving, and communication skills
- Exposure to PySpark, Athena, CloudWatch, SNS, and SQS
- Internship, project, or academic experience specifically in cloud computing, analytics, or data engineering
- Familiarity with cloud-native foundations or AI coding assistants (e.g., GitHub Copilot)
Qualifications
Must Haves
- Degree holders for the visa application process
- 0 to 4 years of software development or data engineering experience across relevant cloud platforms
- Good knowledge of Python and SQL
- Solid understanding of AWS services, specifically S3, SNS/SQS, EMR, Glue, Lambda, Redshift, and Step Functions
- Strong grasp of ETL concepts and data processing fundamentals
- Familiarity with GitLab, Terraform, and the Software Development Life Cycle (SDLC) from development to production
- Familiarity with PySpark, AWS managed services, data engineering best practices, and code optimization
- High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery
- Technologist DNA: A deep understanding of the difference between 'coding' and 'engineering.'
- Good analytical, problem-solving, and communication skills
Nice to Haves
- Exposure to PySpark, Athena, CloudWatch, SNS, and SQS
- Internship, project, or academic experience specifically in cloud computing, analytics, or data engineering
- Familiarity with cloud-native foundations or AI coding assistants (e.g., GitHub Copilot)
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