Big Data Engineers are ubiquitous in every data-driven industry from agriculture to climate change. This template contains the job description, requirements, and responsibilities for the Big Data Engineer job. You can modify them to fit your organization's unique needs.
Big Data Engineer Job Description
We are hiring Big Data Engineers who can build and manage reliable data pipelines through workflow management systems. So, acquaintance with SQL, Perfect, Apache airflow, AWS, REST APIs, and others is a must.
You have to know about data strategies from data lakes to cloud migration. Also, familiarity with containers, command line interfaces, Infrastructure as a Code (IaC), and popular programming languages are what we strongly look for.
Big Data Engineering certifications from AWS, Google Cloud, or Microsoft Azure are an extra advantage.
What are we looking for?
- Advanced degrees in computer science, mathematics, or statistics (good to have)
- Expertise in coding languages like Java, C++, and Python
- Knowledge of algorithms used for predictive modeling, natural language processing (NLP), and text analysis
- Expertise in statistical modeling and analysis and database architecture
- Knowledge of business analytics and intelligence tools like Microsoft Power BI and Azure
- Experience in using Hadoop’s MapReduce compiled language, Hive query language, and Apache Pig scripting language
A Day in the Life of a Big Data Engineer will look like this
- Leverage Data Engineering expertise for multiple teams across our organization
- Establish fault-tolerant, adaptive, and accurate data computational pipelines
- Steer data profiling activities of source system candidates
- Lead efforts to document source-to-target mappings
- Direct efforts to design and implement logical data models focusing on usability
- Configure and ensure conformed dimension design and modeling across the RDS
- Responsible for Performance and ease of use of data and information
- Liaison with other designers and architects to build ergonomic data models
- Write programs in Python for data cleaning and processing activities
- Execute projects through an agile management process
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