ETL DEVELOPER

Kampgrounds Of America, Inc.•Billings, MT

About The Position

The ETL Developer (Extract, Transform, and Load) is responsible for designing, developing, and maintaining robust data integration solutions and transforming KOA data into a format that is consumable by end users and applications. This position builds scalable ETL pipelines, ensuring data accuracy, consistency, and efficient delivery from various sources into the data warehouse for analytics and reporting.

Requirements

Bachelor's degree in Computer Science, IT, or related field (or equivalent experience).
Proven experience in designing and building ETL pipelines.
Experience with cloud data platforms (Azure, AWS, GCP). Strong SQL proficiency and database knowledge (e.g., MS SQL Server, Oracle).
Experience with at least one major ETL tool (Data Factory, SSIS)
Programming skills in Python, Java, or similar.
Understanding of data warehousing concepts and dimensional modeling.
Excellent analytical, problem-solving, and communication skills.

Nice To Haves

Familiarity with CI/CD practices and data governance
Experience with Power BI

Responsibilities

Design and develop data aggregation pipelines that extract data from various sources, transform it into the desired format, and load it into the appropriate data storage systems using tools like Azure Data Factory, SSIS, or custom scripts.
Optimizes data pipelines and data processing workflows for performance, scalability, and efficiency.
Monitor, test, and troubleshoot ETL jobs to ensure high availability, performance, and data quality.
Implements data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of the data.
Collaborate with data scientists and data analysts to optimize models and algorithms for data quality, security, and governance.
Write and optimize complex SQL queries and scripts for data manipulation.
Integrates data from different sources, including databases, data warehouses, APIs, and external systems.
Develop source-to-target mappings and detailed transformation logic.
Transforms raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques.
Ensures data quality and accuracy by performing data validation, monitoring, error-handling processes, and cleaning as needed.
Identifies and implements optimizations to continually enhance query performance, reduce processing time, and increase overall productivity.
Delivers well-defined, transformed, tested, documented, and code-reviewed datasets for analysis.
Collaborate with business analysts and stakeholders to understand data requirements and deliver effective data solutions.