Duties: Develop compelling proofs of concept for data solutions using emerging technologies for real-time and big data ingestion and processing. Contribute to designing, building, and deploying high-performance production platforms/infrastructure to support data warehousing, real-time ETL, and batch big-data processing; help define standards and best practices for enterprise usage. Design, build, and maintain processes and components of streaming data/ETL pipeline to support real-time analytics (from requirements to data transformation, data modeling, metric definition, reporting, etc.). Focus on data quality - detect data/analytics quality issues all the way down to root cause, and implement fixes and data audits to prevent/capture such issues. Collaborate with data scientists to design and develop processes to further business unit and company-wide data science initiatives on a common data platform. Translate business analytic needs into enterprise data models and ETL processes to populate them.
Requires a Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field, plus 5 years of data engineering experience in traditional data warehousing or in big data and pipeline processing environments. Also requires 5 years of experience (for candidates with a Bachelor's degree) or 2 years of experience (for candidates with a Master's degree) of experience with of the following: data modeling; SQL; programming in Python, Scala, or Java; using Spark, Storm, Kafka, Flume, Pig, Hive, Sqoop, or Hadoop/MapReduce; columnar storage; massive parallel processing data warehouses; working within the Amazon Web Services (AWS) ecosystem; working within Agile software engineering methodologies. Employer will accept any suitable combination of education and experience.
Must also have authority to work permanently in the U.S. Applicants who are interested in this position may apply at www.jobpostingtoday.com, Job ID: 58223, for consideration.