Data Engineer

2 weeks ago

Thousand Oaks, United States Gigaedge Inc Full time

Job Expectations:

  1. Create and maintain optimal data pipeline architecture,
  2. Assemble large, complex data sets that meet functional / non-functional business requirements.
  3. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  4. Build the infrastructure required for optimal ingestion, transformation, and Publishing of data from a wide variety of data sources using Python/Spark and AWS ‘big data’ technologies.
  5. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
  6. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  7. Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
  8. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
  9. Work with data and analytics experts to strive for greater functionality in our data systems

Experience Requirements:

  1. Advanced working SQL,Python/PySpark knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  2. Experience building and optimizing ‘Cloud big data’ data pipelines, architectures and data sets.
  3. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
  4. Strong analytic skills related to working with unstructured datasets.
  5. Build processes supporting data transformation, data structures, metadata, dependency and workload management.
  6. A successful history of understaing, processing and extracting value from large disconnected datasets.
  7. Working knowledge of message queuing, stream processing and highly scalable ‘big data’ data stores.
  8. Understating of various data sets Structured ,Semi Structured ,Data at rest /Motion
  9. Experience in Data Modeling
  10. Strong project management and organizational skills.
  11. Experience supporting and working with cross-functional teams in a dynamic environment. and knowledge of one or more from the below
  12. Experience with big data tools: Hadoop, Spark, Kafka, etc.
  13. Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
  14. Experience with data pipeline and workflow management tools: Apache NiFi,AWS Step Function ,Oozie,Azkaban, Luigi, Airflow, etc.
  15. Experience with AWS cloud services: EC2, EMR, RDS, Redshift
  16. Experience with stream-processing systems: AWS DMS, Kinesis, Spark-Streaming, etc.
  17. Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

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