Data Engineer (Entry Level) - US/Canada Residents only, Full-Time, Salary $60K-$70K.
Minimum 1 year of project experience required - fully remote position. Freshers are also encouraged to apply.
About us: The Future of AI is Patterned We are a stealth-mode technology startup that is revolutionizing the way AI is used. Our platform uses pattern recognition to train AI models that are more accurate, efficient, and robust than ever before.
We are backed by top investors and we are hiring for almost everything! If you are passionate about AI and want to be a part of something big, then we want to hear from you.
Make a positive impact on the world. Be a part of a fast-growing startup. If you are interested in learning more, please visit our website.
We Are Looking For People Who Are
Passionate about AI.
Excellent problem solvers.
Team players.
Driven to succeed.
Requirements
Job Description:
We are seeking a motivated and talented Data Engineer to join our team as an Entry Level Data Engineer. As a part of our dynamic data team, you will have the opportunity to work on exciting projects, collaborate with experienced professionals, and contribute to the development of innovative data solutions. This position is ideal for recent graduates or individuals with limited professional experience in data engineering who are passionate about working with data and want to gain valuable experience in a supportive and collaborative environment.
Responsibilities
- Collaborate with the data team to design, build, and maintain data pipelines and data infrastructure
- Extract, transform, and load (ETL) data from various sources into data storage systems
- Develop and maintain data models and database schemas
- Ensure data quality and implement data validation and cleaning processes
- Perform data analysis and provide insights to stakeholders
- Work with cross-functional teams to understand data requirements and deliver solutions that meet business needs
- Stay up-to-date with emerging data technologies and industry trends
- Contribute to improving data engineering best practices and processes
Requirements
- Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field (or equivalent experience)
- Strong understanding of data engineering concepts and principles
- Project work on the technologies needed
- Proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL)
- Familiarity with data processing frameworks (e.g., Apache Spark, Apache Kafka)
- Experience with scripting languages (e.g., Python, R, Scala) for data manipulation and automation
- Knowledge of data warehousing and data modeling concepts
- Understanding of data integration and ETL processes
- Strong problem-solving and analytical skills
- Excellent communication and teamwork abilities
Preferred Qualifications
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and related services (e.g., S3, Redshift, BigQuery)
- Familiarity with data visualization tools (e.g., Tableau, Power BI)
- Knowledge of distributed computing frameworks (e.g., Hadoop, Apache Flink)
- Understanding of data governance and security best practices
- Projects or internships demonstrating your data engineering skills
Benefits
Special Benefits you will love:
- Flexible vacation, unlimited paid holidays, and paid sick days
- 401(k) with up to 2% employer match
- Health, vision, and dental insurance
Why Patterned Learning AI?
Patterned Learning AI is made up of incredibly bright, mission-driven coworkers who are passionate about using technology to solve real-world problems---and we're growing quickly. In order to continue building an engaging and dynamic organization, we're committed to giving everyone the support they need to do great work.
We believe diverse perspectives and backgrounds are critical to building great technology, and our goal is to cultivate an environment where people feel equally valued and respected. Patterned Learning AI is proud to be an equal opportunity workplace, and we welcome applicants from all backgrounds regardless of race, color, ancestry, religion, gender identity or expression, sexual orientation, marital status, age, citizenship, socioeconomic status, disability, or veteran status.
