Hybrid Data Engineer

at VISTRA

• Job title: Data Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Airflow, Amazon Redshift, Apache, AWS, Cloud, Docker, DynamoDB, ElasticSearch, ETL, JavaScript, Kafka, MongoDB, MySQL, Next.js, Node.js, NoSQL, Python, SQL, Tableau
• Location requirements: Hybrid, Singapore

About the role

• Data Engineer at Vistra designing and maintaining data pipelines for analytics. Collaborating with teams and optimizing data integration using modern cloud technologies.

Responsibilities

• 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