Senior Data Engineer

Bachelor’s degree in Computer Information Systems, Electronics and Communication Engineering, or Applied Mathematics
Five (5) years of progressive post-baccalaureate experience in job offered or in an engineer-related occupation
Programming languages, such as Python, Java, and Scala
Big Data Frameworks such as Hadoop, Hive, Spark, and Databricks
ETL Tools including PLSQL
Scripting such as Unix, and PowerShell
Databases such as Oracle, MYSQL, Postgres, Teradata, and Snowflake
Cloud Technologies including AWS Cloud, Azure Cloud, Azure Blob, AWS EMR, AWS EC2, AWS S3, AWS Lambda, AWS Athena, Redshift, Aurora, AWS Kinesis, Kafka, and Spark Streaming
Analytics Tools such as Tableau
Data Security Control using Apache Ranger with Privecera Cloud
Version Control including Git and Bitbucket
Scheduling Tool Airflow

Design and build reusable components, frameworks and libraries at scale to support analytics products
Design and implement product features in collaboration with business and Technology stakeholders
Identify and solve issues concerning data management to improve data quality
Clean, prepare and optimize data for ingestion and consumption
Collaborate on the implementation of new data management projects and re-structure of the current data architecture
Implement automated workflows and routines using workflow scheduling tools
Build continuous integration, test-driven development and production deployment frameworks
Review design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards
Analyze and profile data for designing scalable solutions
Troubleshoot data issues and perform root cause analysis to proactively resolve product and operational issues
Develop architecture and design patterns to process and store high volume data sets
Participate in an Agile / Scrum methodology to deliver high quality software releases through Sprints

No preferred qualifications provided.