ETL Developer

Gunnison Consulting Group•Washington, DC

1d•$100,000 - $107,000

About The Position

This position is contingent on a future opening with Gunnison. Salary: $100,000 - $107,000/year Key Responsibilities: ETL Process Design and Development: Design and implement ETL processes to extract data from various sources, transform it according to business requirements, and load it into target databases or data warehouses. Develop and maintain ETL scripts, stored procedures, and functions. Data Integration and Management: Generate new business insights through data extraction, storage, transformation, analysis, and visualization of diverse data sets. Analyzes data using data mining, machine learning, and statistical algorithms available in COTS tools (e.g. SAS, SPSS, and Oracle); builds analytical solutions using programming languages (e.g. R, Python, SAS), and programming libraries (e.g. Python SciKit, R Caret, PostgreSQL MADlib, Apache Spark MLlib). Ensure data integrity, consistency, and quality throughout the ETL process. Collects and transforms structured, unstructured, relational, and NoSQL data using ETL and ELT tools as well as develops custom code using programming languages. Understands and uses distributed (e.g. MapReduce) methods that scale to multi-Terabyte sized data collections. Interprets and evaluates accuracy of results through iterative, agile methods. Applies data discovery and data visualization tools (e.g. Tableau, Trifacta) to develop compelling, actionable, useful data stories. Works closely with data SMEs, business, and management to prioritize business and information needs.

Requirements

8+ years of directly relevant experience.
Experience working directly on a data science team.
Experience working with tools, including object-oriented programming (Python, Java), computational analysis tools (R, MATLAB), and associated data science libraries (scikit-learn).
Data science methods related to data architecture, data munging, data and feature engineering, and predictive analytics.
Experience creating meaningful data visualizations and interactive dashboards using platforms such as Tableau, Qlik, Power BI, RShiny, plotly, and d3.js to communicate findings and relate them back to how your insights create business impact.
Experience with cloud-based ETL solutions (e.g., AWS Glue, Azure Data Factory).
Knowledge of Big Data technologies (e.g., Hadoop, Spark).
Bachelors Degree in data science, mathematics, statistics, economics, computer science, engineering, or other related business or quantitative discipline is required.
May substitute with commensurate experience (+4 years).
Certification in relevant ETL or data integration technologies.
Ability to obtain and maintain a Public Trust.

Nice To Haves

Bachelor’s degree in Computer Science, Information Technology, or a related field.
Equivalent experience may be considered.

Responsibilities

ETL Process Design and Development: Design and implement ETL processes to extract data from various sources, transform it according to business requirements, and load it into target databases or data warehouses.
Develop and maintain ETL scripts, stored procedures, and functions.
Data Integration and Management: Generate new business insights through data extraction, storage, transformation, analysis, and visualization of diverse data sets.
Analyzes data using data mining, machine learning, and statistical algorithms available in COTS tools (e.g. SAS, SPSS, and Oracle); builds analytical solutions using programming languages (e.g. R, Python, SAS), and programming libraries (e.g. Python SciKit, R Caret, PostgreSQL MADlib, Apache Spark MLlib).
Ensure data integrity, consistency, and quality throughout the ETL process.
Collects and transforms structured, unstructured, relational, and NoSQL data using ETL and ELT tools as well as develops custom code using programming languages.
Understands and uses distributed (e.g. MapReduce) methods that scale to multi-Terabyte sized data collections.
Interprets and evaluates accuracy of results through iterative, agile methods.
Applies data discovery and data visualization tools (e.g. Tableau, Trifacta) to develop compelling, actionable, useful data stories.
Works closely with data SMEs, business, and management to prioritize business and information needs.