Remote, but you must be in the following location
Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world.
The Data Engineer will be responsible for architecting, designing, and implementing advanced analytics capabilities. The right candidate will have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards, be comfortable using visualization tools, and be able to apply your skills to generate insights that help solve business challenges. We are looking for someone who can bring their vision to the table and implement positive change in taking the company's data analytics to the next level.
6+ years of experience in a Data Engineer role
Experience with Big Data Technologies - Hadoop, Hive, Hbase, Pig Spark, etc.
Highly Skilled in Python (NumPy, Pandas, scikit-leam, Dash, Dask, Flask, Boto3, etc.)
Experience with Hive, presto, Pyspark, Scala and AWS ecosystem for big data
Very comfortable with big data concepts i.e., volume, data and speed of data delivery
Experience extracting/querying/joining large data sets at scale
AWS Certification is plus
Experience with large Pharma Institutions is preferred
A desire to work in a collaborative, intellectually curious environment
Strong communication and organizational skills
Bachelor's degree in Computer Science or similar field
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility.
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