What are the responsibilities and job description for the Data Modeler position at Tech Army?
Skills Matrix Key Knowledge, Skills, and Abilities
5-7 years' experience in data engineering, including designing and implementing data pipelines and ETL processes.
Proficiency with Alteryx. (Proficiency level - 5)
Proficiency in programming languages such as Python and SQL. (Proficiency level - 4)
Strong analytical and problem-solving skills, with the ability to analyze complex datasets and extract actionable insights. (Proficiency level - 4)
Knowledge of relational database design and data modeling. (Proficiency level - 4)
Ability to establish and maintain effective working relationships with others. (Proficiency level - 3) Ability to work independently. (Proficiency level - 3)
to determine work priorities and ensure proper completion of work assignments. (Proficiency level - 3)
Ability to communicate effectively, both verbally and in writing. (Proficiency level - 3)
Familiarity with environmental science, water quality, or related fields. Experience with implementing data warehouses, data lakes, or data lakehouses Experience with business intelligence tools such as Qlik Sense.
Education : Bachelor's or master's degree in Data Science, Computer Science, Information Systems or other Information Technology major, or equivalent work experience.
Required Tasks to be performed :
Design, implement, and maintain robust data pipelines and architectures in Alteryx Designer.
Create and maintain logical data models in Oracle SQL Developer Data Modeler.
Read, write, and update data.
Create and maintain ETL code repository.
Perform ad hoc data cleansing of data sets as needed.
Develop and implement data quality control procedures to ensure the accuracy, completeness, and consistency of environmental data.
Define data quality standards and metrics.
Execute procedures to monitor data quality.
Identify data issues and propose remediation plans.
Optimize data processing workflows and algorithms for efficiency, scalability, and reliability.
Configure SAS Viya analytics platform as needed.
Ensure compliance with data privacy regulations and security best practices in data handling, storage, and transmission.
Stay current with emerging technologies, tools, and methodologies in data engineering and environmental science.
Collaborates with data scientists and analysts to optimize models and algorithms for data quality, security, and governance.
Monitors and tunes data systems, identifies and resolves performance bottlenecks, and implements caching and indexing strategies to enhance query performance.
Transforms raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques. Establishes the governance of data and algorithms used for analysis, analytical applications, and automated decision making.
Provide leadership, guidance, and mentorship to junior staff members and colleagues, fostering a culture of continuous learning, innovation, and excellence in D&A practices.
Required Knowledge, Skills & Abilities (KSAs) :
5-7 years' experience in data engineering, including designing and implementing data pipelines and ETL processes.
Proficiency with Alteryx Designer. (Proficiency level - 5)
Proficiency in programming languages such as Python and SQL. (Proficiency level - 4)
Strong analytical and problem-solving skills, with the ability to analyze complex datasets and extract actionable insights. (Proficiency level - 4)
Knowledge of relational database design and data modeling. (Proficiency level - 4)
Ability to establish and maintain effective working relationships with others. (Proficiency level - 3) Ability to work independently. (Proficiency level - 3)
Ability to determine work priorities and ensure proper completion of work assignments. (Proficiency level - 3)
Ability to communicate effectively, both verbally and in writing. (Proficiency level - 3) Preferred Knowledge, Skills & Abilities (KSAs) :
Familiarity with environmental science, water quality, or related fields.
Experience with implementing data warehouses, data lakes, or data lakehouses.
Experience with business intelligence tools such as Qlik Sense.
