Principal Data Engineer – (Hadoop/Big Data, AWS, Python, Kinesis) - Irvine, CA - Onsite - Contract to Hire - AS
Central Business Solutions•Irvine, CA
•Onsite
About The Position
The Data Engineer will be responsible for all aspects of data acquisition, data transformation, analytics scheduling, and operationalization to drive high-visibility, cross-division outcomes. This role involves investigating, evaluating, testing, and recommending technical solutions for future systems. The engineer will support software developers, database architects, and data scientists on data initiatives and contribute to optimal data delivery architecture.
Requirements
- Bachelor’s degree in computer science, computer engineering, or a related technical field.
- 12+ years of professional experience as a data software engineer; or 16+ years of related experience as a data software engineer in lieu of 4-year degree.
- 2+ years of experience with AWS cloud or other cloud Big Data computing design, provisioning, and tuning.
- Previous experience as a Data Engineer / Database Administrator and/or Business Intelligence Analyst.
- Expertise in database concepts, object and data modeling techniques and design principles.
- Expertise in database architectures, software, and facilities.
- Expertise with programming languages - Python (required), Scala, Ruby, R.
- Database technologies - SQL, performance tuning concepts, AWS RDS, RedShift, MySQL.
- Expertise with big data batch processing tools: Hadoop MapReduce, ElasticSearch, PIG, Hive, Cascading/Scalding, Apache Spark, AWS EMR.
- Expertise with stream-processing systems: Kinesis, Kafka, MQTT.
- Expertise with relational NoSQL databases including DyanamoDB.
- Expertise in writing JSON, XML, YAML and other data definition schemas.
- Excellent verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information and provide advice to management.
- Ability to work on advanced complex technical projects or business issues requiring state of the art technical knowledge or industry.
- Ability to work on significant and unique issues where analysis of situations or data requires an evaluation of intangibles.
- Exercises independent judgment in methods, techniques and evaluation criteria for obtaining results.
- Ability to lead and mentor junior engineers and colleagues.
Nice To Haves
- Related AWS certification, preferred.
Responsibilities
- Lead the creation of data environments and/or data sets to serve a wide range of data users, including Data Scientists, Data Analysts, and Business Analysts.
- Perform offline analysis of large data sets using components of a big data software ecosystem.
- Validate the solution of root cause analysis escalated by various technical staff in multiple organizations.
- Investigate, evaluate, test, and recommend technical solutions for future systems.
- Own product data sets from the definition phase through to production deployment (end-to-end).
- Provide solutions for the design and implementation of Hadoop EMR Cluster/ Big Data Infrastructure.
- Deploy Hadoop/Big Data/Spark and database storage Infrastructures in AWS cloud.
- Monitor HDFS/Hadoop/Spark and related software releases, third-party utilities with emphasis on overall system performance.
- Lead and develop tools and procedures to monitor and automate system tasks on servers and clusters.
- Lead and collaborate with other teams to design, develop, and deploy data tools that support both operations and product use cases.
- Lead and design distributed, scalable, and reliable data pipelines that ingest and process data at scale and in real-time.
- Lead and design big data technologies and prototype solutions to improve data processing architecture.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
