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Job Requirements of Lead Data Engineer:
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Employment Type:
Full-Time
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Experience:
6 years
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Education:
4 Year Degree
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Location:
Chicago, IL (Onsite)
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Lead Data Engineer
EDUCATION/EXPERIENCE REQUIREMENTS
Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or a related field, plus at least six (6) years of progressive experience in data science, analytics, or performance management, including two (2) years of team leadership or mentoring experience, or an equivalent combination of education and experience.
PHYSICAL REQUIREMENTS
- Requires sitting for extended periods of time, standing, visual acumen, manual dexterity, and fingering for working with computer keyboards.
- Requires remaining in a stationary position for extended periods of time and constantly operating a computer and other office productivity machinery.
KNOWLEDGE, SKILLS, AND ABILITIES
- Advanced knowledge of various data programming languages and frameworks (Python, SQL, Java, JavaScript, PHP, C#/.NET, VueJS, etc.).
- Advanced experience in custom and/or industry-standard data migration, integration, and ETL tools and techniques.
- Advanced knowledge of big data frameworks and tools (Hadoop, Spark, MongoDB, Cassandra, etc.)
- Advanced knowledge of programming development requirements and use of source/revision control systems (Git, Mercurial, etc.)
- Advanced knowledge of cloud-based data infrastructure (AWS, Azure, Google, Vertica)
- Advanced knowledge of a range of RDBMS platforms (Postgres, Redshift, DynamoDB, Oracle, SQL Server, MySQL, DB2, etc.)
- Advanced knowledge of specialized database architectures and computing environments.
- Advanced knowledge of continuous delivery and deployment pipelines.
- Advanced analytical, problem-solving, and decision-making skills.
- Advanced report preparation and presenting skills.
- Advanced oral and written communication skills to communicate recommendations to enable decision-making.
- Advanced collaboration skills with cross-functional stakeholders to understand the business usage of data.
- Working knowledge of artificial intelligence (AI) and machine learning.
- Advanced interpersonal and team skills across a variety of fields and management levels.
- Advanced project management skills.
- Advanced organization and time management skills.
- Strong ability to effectively analyze and translate data engineering challenges to the business.
- Strong ability to manage large amounts of data and attention to detail.
- Strong ability to multitask competing projects and deadlines for completion.
WORKING CONDITIONS
- General office environment.
- Required to travel to various CTA field locations and transit property locations.
- Subject to typical field conditions such as noise, dust, grease, and moving vehicles when on-site.
EQUIPMENT, TOOLS, AND MATERIALS UTILIZED
- Standard office equipment.
- Personal computer and related software (MS Word, PowerPoint, Excel, Power BI).
Final salary will be determined in part by the qualifications of the selected candidate and may be higher or lower than target.
Applicants, if hired,must comply with CTA's residency ordinance.
CTA IS AN EQUAL OPPORTUNITY EMPLOYER
No employee or applicant for employment will be discriminated against because of race, color, creed, religion, sex, marital status, national origin, sexual orientation, ancestry, age, unfavorable military discharge, disability or any other status protected by federal, state, or local laws; except where a bona fide occupational qualification exists We are committed to providing an inclusive environment for our workforce and supporting the communities we serve. CTA will make reasonable accommodations for the known disabilities of otherwise qualified applicants for employment as well as its employees, unless undue hardship would result. If you require an accommodation in the application or hiring process, please contact
During the hiring process, CTA's Human Resources department will contact candidates with next steps . Failure to respond to these correspondences in a timely fashion may result in your application being closed out for non-responsiveness.
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