Data Engineer 3
4 weeks ago
Data engineers are mainly tasked with transforming data into a format that can be easily analyzed. They do this by developing, maintaining, and testing infrastructures for data generation. Data engineers work closely with data scientists and are largely in charge of architecting solutions for data scientists that enable them to do their jobs.
Data engineers generally have a bachelor's degree in computer science, information technology, or applied math, as well as a few data engineering certifications like Azure Certified Data Engineer. In addition, data engineers possess a plethora of technical skills and the ability to approach problems in a creative manner.
Working with significant independence and under general direction, position is responsible for the data management and design, implementation, maintenance and monitoring of database technologies and related software. Provides direct support to application and analytics teams. Conducts analysis, creates system specifications, develops, tests and implements engineering, scientific and business applications, operating systems, and file/database servers. Utilizes existing or new technology in the automation of processes. Evaluates software packages and provides recommendations to management. Provides actionable recommendations for improvements in application performance after analyzing underlying database-related infrastructure components. Write and maintain comprehensive documentation, including database dependencies, database inventory, basic database troubleshooting, and daily database operations documents. Recommends and implements improvements of client accessibility to corporate information.
Responsibilities of this position include the following:
- Designs, codes, tests, documents, implements and maintains data lake utilities.
- Supports vendor-developed database implementation and periodic maintenance releases as required.
- Provides technical input to assist in development of project planning.
- Maintains data lake software at appropriate vendor-supported levels.
- Supports data management, movement, security, and performance.
- Implements data pipelines within Azure Data Factory.
- Participate in on-call rotation, including after hour and weekend support.
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Python.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
- Experience building and optimizing big data' data pipelines, architectures and data sets.
- Performs additional responsibilities as requested or assigned.
Requirements for this position include the following:
- Bachelor's degree in computer science, information technology or related field; or equivalent work experience. (Typically four years of additional related, progressive work experience would be needed for candidates applying for this position who do not possess a bachelor's degree.)
- 5+ years of experience in one of the following or any combination of: ADLS, Python, Hadoop, SQL, Databricks, Oracle Fusion Middleware, Azure DevOps, GitHub, ML Studio, Oracle Cloud Infrastructure
- Demonstrated knowledge of backup and recovery, disaster recovery, high availability, security, infrastructure, performance tuning, lifecycle, data management and data movement.
- Effective oral and written communication skills fostering an atmosphere of teamwork, high productivity and accuracy.
- Consistently delivers requirements and meets timelines.
- Advanced analytical and problem-solving skills.
- Ability to prioritize and handle multiple tasks and projects concurrently.
Additional Information
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