VISTRA

Data Engineer

VISTRA

full-time

Posted on:

Location Type: Hybrid

Location: Singapore

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Tech Stack

AirflowAmazon RedshiftApacheAWSCloudDockerDynamoDBElasticSearchETLJavaScriptKafkaMongoDBMySQLNext.jsNode.jsNoSQLPythonSQLTableau

About the role

  • Design and implement scalable ETL/ELT pipelines using AWS services including AWS Glue, Lambda, S3, and Step Functions
  • Build and optimize data integration processes connecting MySQL databases, APIs, and external data sources to analytical systems and data warehouses
  • Develop automated data quality monitoring, validation, and cleansing processes
  • Create and maintain data models, schemas, and documentation to support analytics teams
  • Implement real-time and batch data processing solutions using serverless architectures
  • Collaborate with development teams to integrate data collection points into Next.js applications and Node.js services
  • Build and maintain data analytics APIs and services
  • Monitor data pipeline performance, troubleshoot issues, and implement proactive alerting and logging mechanisms
  • Design and implement data backup, archival, and disaster recovery strategies
  • Work with data analysts and business stakeholders to understand reporting requirements

Requirements

  • Bachelor’s degree in Computer Science, Data Engineering, Mathematics, or a related technical field
  • 4-6 years of hands-on data engineering experience with strong proficiency in Python for data processing, transformation, and pipeline development
  • Extensive experience with AWS data services including AWS Glue, Lambda, S3, Athena, Redshift, and Kinesis for building serverless data pipelines
  • Strong SQL skills and experience with MySQL database design, optimization, and administration including performance tuning and query optimization
  • Experience with data pipeline orchestration tools such as Apache Airflow, AWS Step Functions, or similar workflow management systems
  • Proficiency in data formats including JSON, CSV, Parquet, and Avro
  • Knowledge of data warehousing concepts, dimensional modeling, and analytics best practices for supporting business intelligence requirements
  • Experience with version control systems, CI/CD pipelines, and infrastructure as code practices for deploying and managing data infrastructure
  • AWS certifications such as AWS Certified Data Analytics Specialty or AWS Certified Solutions Architect
  • Experience with streaming data technologies including Apache Kafka, AWS Kinesis, or real-time data processing frameworks
  • Knowledge of machine learning workflows and experience building data pipelines that support ML model training and inference
  • Familiarity with business intelligence tools such as Tableau, Power BI, or AWS QuickSight for creating data visualizations and dashboards
  • Experience with containerization technologies like Docker and orchestration platforms for deploying data processing applications
  • Understanding of data governance, privacy regulations, and security best practices for handling sensitive data in cloud environments
  • Experience with NoSQL databases such as DynamoDB, MongoDB, or Elasticsearch for handling unstructured data and high-volume analytics workloads
Benefits
  • Flexible hybrid working arrangement
  • Birthday leave
  • Comprehensive medical insurance and dental coverage
  • Wellness allowance
  • Competitive annual leave entitlement
  • Internal mentorship program
  • Reimburse professional membership fees for certifications
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
ETLELTPythonSQLMySQLAWS GlueAWS LambdaAWS S3Apache Airflowdata modeling
Soft Skills
collaborationtroubleshootingcommunicationproblem-solvingorganizational skills
Certifications
AWS Certified Data Analytics SpecialtyAWS Certified Solutions Architect