Staff Software Engineer, Data Platform
T
TwilioCommunications
United StatesFull-TimeStaff
Salary171120 - 213900 USD per year
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Job Details
- Experience
- 8+ years
- Required Skills
- AWSPythonHadoopJavaKafkaSparkScala
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 8+ years of experience in software development, or a related field
- Proven track record of architecting and delivering complex data projects at scale, with a deep understanding of data infrastructure and distributed systems
- Expertise in big data technologies such as Hadoop, Spark, Kafka, and other distributed computing systems
- Experience designing, building, and operating large-scale systems using AWS technologies
- Proficiency in programming languages such as Python, Java, or Scala, with strong problem-solving skills and attention to detail
- Experience designing or working with Data Lakehouse architectures, including hands-on experience with Hudi, Iceberg, or Delta data formats
- Excellent communication and collaboration skills, with the ability to influence technical decisions and drive alignment across teams
- Strong leadership skills, with a track record of mentoring and developing junior engineers
- Demonstrated ability to thrive in a fast-paced, dynamic environment and deliver results under tight timelines
Responsibilities
- Serve as a subject matter expert in distributed systems, data technologies, with strong software engineering skills
- Architect and implement scalable and efficient data systems, storage solutions, and processing frameworks using state-of-the-art technologies
- Drive technical innovation and research to stay at the forefront of emerging data technologies and best practices
- Mentor and coach a team of talented engineers, fostering a culture of technical excellence, collaboration, and continuous learning
- Collaborate closely with cross-functional teams to understand business requirements and translate them into scalable and efficient technical solutions
- Ensure data quality, integrity, and security throughout the data lifecycle, adhering to industry best practices and compliance standards
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