Senior Applied Data Engineer
As the Senior Applied Data Engineer of the Data Science & Engineering team, you will develop data products and solutions that sit atop vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms, cutting-edge machine learning techniques including deep learning, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses with a keen eye for data privacy. You will have the opportunity to create high performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data.
You will have the opportunity to develop data-driven innovative analytical solutions and identify opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations/decisions through activities like AI-driven engineering solutions, automated data pipelines, performing jobs in big data cluster by using different execution engines such as Spark, Hive, Impala, etc.
Job Description
- Experience in building, deploying, and maintaining production-level data- driven application and data processing workflows or pipelines.
- Experience with testing frameworks and test-driven development (TDD) practices.
- Understand product requirements, engage with team members and customers to define solutions, and estimate the scope of work required.
- Ability to quickly learn and implement new technologies and perform POC to explore best solution for the problem statement.
Qualifications
- Bachelor's Degree in Computer Science, Applied Mathematics, Engineering or related field.
- You have at least 4 years of experience, ideally within a Software Engineer, Data Engineer and/or Data Solution role.
- High proficiency in Python, Pyspark and SQL.
- Experience in the cloudnative big data frameworks like Hadoop, Yarn, Spark, Impala, Hive, NiFi, Airflow
- Experience working with engineering best practices like Git, Jira, DevOps
- Solid understanding of data modelling, data monitoring, data dashboarding, database design, and data warehousing concepts.
Rupa Kankariya EA License No. 02C3423 Personnel Registration No. R1441955
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