Job Responsibilities:
- Be a thought leader and forward thinker, help drive an innovative vision for our various products and platforms, design and launch strategic data mining solutions and drive business-wide innovation.
- Take the lead in the end-to-end software development lifecycle, encompassing design, testing, deployment, and operations, lead technical discussions and strategy, and participate hands-on in design reviews, code reviews, and implementation.
- Transform vast amounts of raw data into actionable insights by developing scalable, efficient, and automated processes and tools for large-scale data analyses, metadata discovery, data integrity and accuracy.
- Design and develop large-scale knowledge graphs through semantically linking information and datasets from across multiple product and technical domains.
- Mentor and develop other engineers on the team, establish technical direction and foster team culture.
- Uphold the highest standards of technical rigor in engineering and operational excellence, build highly resilient and scalable systems, and champion operational and process improvements.
Basic Qualifications:
- Degree in mathematics/computer science or related discipline.
- 4+ years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments and operations.
- 4+ years of experience in programming, with proficiency in at least one programming language, preferably Python or Java.
- 3+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud).
- Experience working with distributed and big data technologies (e.g. MapReduce, Spark, Flink, Kafka, PySpark, NoSQL, etc.).
- Experience as a mentor, tech lead or leading an engineering team.
- Adept at tackling highly complex, ambiguous or undefined problems.
Preferred Qualifications:
- MS or PhD in Computer Science or equivalent experience.
- Experience dealing with real world large-scale datasets.
- Strong understanding and passion for statistical/mathematical modelling and data analysis.
- Prior experience working with graph data, and graph databases.
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