Data Engineer
qode.world
full-time
Posted on:
Location Type: Hybrid
Location: New York City • New York • Ohio • United States
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About the role
- Analyzing and organizing raw data to identify trends and patterns.
- Developing and maintaining robust and scalable datasets for various analytical purposes.
- Improving data quality and efficiency through data cleansing and validation techniques.
- Building and maintaining data systems and pipelines to ensure seamless data flow.
- Evaluating business needs and objectives to align data engineering efforts with strategic goals.
- Interpreting trends and patterns in data to provide actionable insights.
- Conducting complex data analysis and reporting on results to stakeholders.
- Preparing data for prescriptive and predictive modeling to support advanced analytics.
- Building algorithms and prototypes to explore new data-driven solutions.
- Combining raw information from different sources to create consistent, machine-readable formats.
- Exploring ways to enhance data quality and reliability through innovative techniques.
- Identifying opportunities for data acquisition to expand the scope of available data.
- Developing analytical tools and programs to empower data users.
- Collaborating with data scientists and architects on various projects to deliver comprehensive data solutions.
Requirements
- Technical expertise with data models, data mining, and segmentation techniques.
- Strong analytical and problem-solving skills with the ability to work with complex datasets.
- Hands-on experience with SQL database design and optimization.
- Proficiency in programming languages such as R and Python for data manipulation and analysis.
- Bachelor’s Degree in Computer Science, IT, or a related field.
- Highly motivated with a strong sense of ownership and accountability.
- Quick learner with a positive attitude and a willingness to embrace new technologies.
- Genuine team player with excellent communication and collaboration skills.
- Ability to communicate effectively with both technical and non-technical audiences.
- Experience with cloud-based data platforms (e.g., AWS, Azure, GCP) is a plus. (Inferred)
- Familiarity with data warehousing concepts and ETL processes. (Inferred)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data analysisdata cleansingdata validationdata modelingdata miningsegmentation techniquesSQLRPythonETL
Soft Skills
analytical skillsproblem-solvingownershipaccountabilityquick learnerpositive attitudeteam playercommunication skillscollaboration skillsability to communicate with technical and non-technical audiences