Data Engineer

Key Responsibilities:

Core Development Practices:

• Actively contribute as a hands-on coder, with substantial experience in programming languages like Python or PySpark.
• Gain practical experience with the Big Data ecosystem, including technologies such as Hadoop, Mapreduce, Spark, Hbase, and ElasticSearch.
• Exhibit a robust understanding of programming principles and development best practices, including check-in policies, unit testing, and code deployment.
• Demonstrate initiative as a self-starter, capable of quickly absorbing new concepts and technologies and translating them into scalable engineering solutions.
• Possess excellent experience in application development, support, integration development, and data management.

Client Engagement:

• Interact daily with clients from leading Fortune 500 companies to thoroughly understand their strategic requirements and align Sigmoid's contributions with key client initiatives.

Technological Advancement:

• Maintain up-to-date knowledge of the latest technological advancements to ensure optimal Return on Investment (ROI) for both our customers and Sigmoid.
• Function as a hands-on coder with a strong grasp of enterprise-level code standards.
• Design and implement APIs, abstractions, and integration patterns to effectively address complex distributed computing challenges.
• Leverage experience in defining technical requirements, data extraction, data transformation, automating jobs, productionizing workflows, and exploring new big data technologies within a parallel processing environment.

Cultural Attributes:

• Employ strategic thinking and an unconventional, out-of-the-box approach to problem-solving.
• Maintain an analytical and data-driven orientation.
• Exhibit essential qualities of raw intellect, talent, and energy.
• Embrace an entrepreneurial and agile mindset, understanding the demands of a private, high-growth company.
• Demonstrate the ability to excel as both a leader and a hands-on contributor.

Qualifications:

• A proven track record of relevant work experience, coupled with a degree in Computer Science or a related technical discipline, is required.
• Mandatory experience with functional and object-oriented programming in Python or PySpark.
• Hands-on experience with the Big Data stack, including Hadoop, Mapreduce, Spark, Hbase, and ElasticSearch.
• Solid understanding of AWS services and practical experience working with APIs and microservices.
• Effective written and verbal communication skills.
• Ability to collaborate seamlessly with a diverse team of engineers, data scientists, and product managers.
• Comfort and adaptability in a fast-paced start-up environment.

Preferred Qualifications:

• Experience working within agile methodologies.
• Proficiency in database modeling and development, data mining, and data warehousing.
• Experience in the architecture and delivery of enterprise-scale applications, with the capability to develop frameworks and design patterns. Must be able to comprehend and address technical challenges, propose comprehensive solutions, and mentor junior staff.
• Experience managing and processing large, complex datasets from a wide array of sources.