Data Engineer
Date: Jun 13, 2022
Location: Irvine, California, US, 92606
Company: Kia America, Inc.
At Kia, we’re creating award-winning products and redefining what value means in the automotive industry. It takes a special group of individuals to do what we do, and we do it together. Our culture is fast-paced, collaborative, and innovative. Our people thrive on thinking differently and challenging the status quo. We are creating something special here, a culture of learning and opportunity, where you can help Kia achieve big things and most importantly, feel passionate and connected to your work every day.
Kia provides team members with competitive benefits including premium paid medical, dental and vision coverage for you and your dependents, 401(k) plan matching of 100% up to 6% of the salary deferral, and time off starting at 14 days per year. Kia also offers company lease and purchase programs, company-wide holiday shutdown, paid volunteer hours, and premium lifestyle amenities at our corporate campus in Irvine, California.
Status
Summary
As Kia North America’s Big Data Center continues to grow rapidly, we are looking to add a talented Data Engineer to our team. The position will be responsible for building ETL data pipelines for use in machine learning models and visualizations. This will require participating in the full development lifecycle (design, implementation, testing, documentation, delivery, support, and maintenance).
Major Responsibilities
1st - Build robust and scalable data pipelines. (30%)
2nd - Maintain existing data pipelines especially on telematics data. (20%)
3rd - Dataset documentation. (20%)
4th - Solve database performance issues. (20%)
5th - Build APIs. (10%)
Education/Certification
- Bachelor’s degree in computer science, statistics, engineering, informatics, information systems or similar technical discipline.
- Certifications in Data Engineering.
Overall Experience
N/A
Directly Related Experience
- Advanced SQL knowledge and experience with relational databases.
- Experience with Hadoop ecosystem (Hadoop, Hive, Impala and Spark etc.).
- Experience with data modeling, data warehousing, and building ETL pipelines.
- Experience with shell scripting.
- Experience working in a UNIX/LINUX environment.
- Proficient in the use of Python and libraries used for parallel computing (e.g. Dask).
- 2+ years of experience working as a Data Engineer or in a similar role.
Preferred Experience:
- Familiarity with machine learning concepts.
- Experience with Apache Airflow.
- Proficiency with Scala.
- Experience using visualization tools (e.g. Power BI, MicroStrategy, Tableau etc.).
- Master’s degree.
Skills
Competencies
Equal Employment Opportunities
KUS provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, ancestry, national origin, sex, including pregnancy and childbirth and related medical conditions, gender, gender identity, gender expression, age, legally protected physical disability or mental disability, legally protected medical condition, marital status, sexual orientation, family care or medical leave status, protected veteran or military status, genetic information or any other characteristic protected by applicable law. KUS complies with applicable law governing non-discrimination in employment in every location in which KUS has offices. The KUS EEO policy applies to all areas of employment, including recruitment, hiring, training, promotion, compensation, benefits, discipline, termination and all other privileges, terms and conditions of employment.
Disclaimer: The above information on this job description has been designed to indicate the general nature and level of work performed by employees within this classification and for this position. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job.
Nearest Major Market: Irvine California
Nearest Secondary Market: Los Angeles
Job Segment:
Data Analyst, Data Modeler, Data Warehouse, Data Center, Computer Science, Data, Technology