Data Engineer

Summary

Join AccelOne as a Data Engineer and design, build, and maintain real-time and batch data pipelines using Kafka, AWS, and Python. You will collaborate with cross-functional teams to develop data products and ensure reliable, scalable, and high-performance data infrastructure. This role demands expertise in data modeling, schema design, and performance optimization, along with proficiency in Python data libraries. Experience with AWS services, event-driven architectures, and Agile development is essential. AccelOne offers remote work, professional growth opportunities, and a supportive, inclusive environment.

Requirements

• 4+ years of experience as a data engineer in a production environment
• Fluency in Python, with strong experience in a Linux environment
• Strong SQL skills, with hands-on experience in Snowflake and MySQL
• Solid understanding of data modeling, schema design, and performance optimization
• Proficiency with Python data libraries: NumPy, Pandas, SciPy
• Experience building and maintaining real-time data pipelines using Kafka (Apache Kafka or AWS MSK)
• Familiarity with AWS services including Lambda, Kinesis, S3, and CloudWatch
• Experience working with event-driven architectures and streaming data patterns
• Knowledge of RESTful APIs, data integration, and version control workflows (e.g., Git)
• Comfortable in Agile development environments with strong testing and code review practices

Responsibilities

• Design, build, and maintain scalable real-time and batch data pipelines using Kafka, AWS, and Python
• Develop event-driven data workflows leveraging Kafka topics, Lambda functions, and downstream sinks (e.g., Snowflake, S3)
• Work with cross-functional teams to translate business requirements into reliable data products
• Build and maintain robust ETL processes across Snowflake and MySQL for reporting and analytics
• Ensure high-quality data delivery by writing modular, well-tested Python code
• Monitor data pipelines using tools such as CloudWatch, Grafana, or custom metrics
• Contribute to technical design, architectural reviews, and infrastructure improvements
• Maintain data integrity and scalability in a high-volume data environment
• Continuously explore and implement best practices in data engineering, streaming, and analytics infrastructure

Benefits

• Remote Work : Enjoy flexibility and a competitive compensation package
• Professional Growth : Access to career development opportunities, training, and certifications
• Inclusive Environment : We foster a people-first culture where everyone can thrive professionally and personally