Data Engineer- ADVISOR
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Job description
A NASDAQ-listed company that has been a trend-setter in the transportation business, is looking for a Data Engineer (Advisor). The engineer will contribute to the creation of and adherence to technical standards for data engineering, including the selection and refinements of foundational technical components. The globally established company commands a workforce of more than 500,000 employees and has branched out their services to now offer shipping, e-commerce and other business services along with transportation. This is a great opportunity to work with global IT leaders, businesses, software engineers and data scientists, while rising quickly through the ranks.
Job Responsibilities:
- Quickly get up-to-date with business and technical hurdles required to be solved with DataWorks
- Develop tools, platforms, and pipelines to help teams to analyze data, build models and make decisions
- Keep producing tangible rapid growth, while partnering with different professionals and teams
- Deploy the best coding practices to ensure reusability in the form of accessible, reusable patterns, templates, and code-bases
- Stay updated with leading technologists of different enterprises to develop with time and ensure smooth deployments to downstream operational systems
Job Requirements:
- Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
- At least 7 years of experience in measuring and analyzing, finding quantitative business solutions, handling simulation developments, and/or predictive analytics
- Well-versed with data engineering and machine learning frameworks for designing, developing, and implementing complex systems and data pipelines
- In-depth knowledge of designing, developing, and implementing large batch or online transaction-based systems
- Familiarity with the transportation industry, the competitors, and associated new technologies
- Experience working as a leader in general planning or in consulting setting
- Strong knowledge of distributed and cloud environments
- Skilled at technologies like Spark (Scala and PySpark), Kafka, HDFS, and other high volume data tools
- Proficiency with SQL and NoSQL storage tools, such as PostgreSQL, MySQL, Cassandra, ElasticSearch, and MongoDB
- Experience working with tools like Matplotlib, Pandas, TensorFlow, Scikit-Learn, Jupyter and other Python data tools
- Deep understanding of balancing computational considerations with theoretical properties
- Expertise in Microsoft Azure tooling for large-scale data engineering efforts and deployments is desirable
- Experience in building and deploying robust, complex production systems that implement modern, data scientific methods at scale
- Prior experience of working as a senior member of multi-function project teams
- Strong communication and documentation skills with fluency in English
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