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.
Applicants who are interested in this position may apply online at www.jobpostingtoday.com, Reference# 87559.