Data Engineer (SQL/Python ETL Modernization)

Mavensoft Technologies.•Salem, OR

19h•Remote

About The Position

The Data Engineer will be responsible for the extraction and analysis of company information, primarily financial, personal, expense, and revenue reports. This role involves writing data collection and processing procedures, ensuring data is correctly gathered, stored, and analyzed, and reporting data findings to management. The engineer will continually monitor data collection and develop methodologies to improve data analysis. A key part of this role is to perform analysis of the HAL data system, which may include reviewing documentation and analyzing the current HAL system/environment, including data models, schemas and tables, data dictionaries, ETLs, system and database management processes, data quality, security, queries, and the reporting environment. The engineer will work with OHA project team members (PM, BAs, DBAs, data analysts, architects), HAL management, and HAL users to identify and determine business/technical requirements. They will gather and document detailed system, data, and integration requirements for HAL system improvements (e.g., changes to ETL code, business rules, HAL tables, new or updated OHG Medicaid claim code grouping categories, etc.). The role also includes designing, developing, and implementing data pipelines using ETL processes and SQL tables that extract, transform, and load data into a HAL Medicaid data system/datamart that helps the organization reach its strategic goals. A significant responsibility is to migrate existing ETL processes built in legacy SAS coding to the Microsoft Structured Query Language (“SQL”) stack and Python language/stored procedures. This migration involves working with various program areas and business teams to make code as modular as possible, reviewing and analyzing existing ETL SAS programming code to update to new SQL/Python language/procedures, and developing new SQL stack/stored procedures programming code to create new ETL processes. Finally, the engineer will test, troubleshoot, and implement the new ETL code in the HAL test and production environments.

Requirements

SQL programming language
Python programming language
Advanced data analysis skills.
Experience using Microsoft DevOps, GIT or other code management tools.
Bachelor’s degree in finance, math, or data science.
Hands-on knowledge of database tools SQL.
Knowledge of programming languages like Python, Java, and R.
Excel, Agile, Data modeling, Data analytics, Data mining, Data visualization.
Familiarity with analytical tools like SAS, Hadoop, Spark, Hive, and Pig that may assist businesses in developing a solid BI strategy

Nice To Haves

SAS programming language
Experience using Jupyter Notebooks
Data Warehousing
Good communication skills

Responsibilities

Extraction and analysis of company information, primarily financial, personal, expense, and revenue reports.
Writing data collection and processing procedures.
Ensuring that data is being correctly gathered, stored, and analyzed.
Reporting data findings to management.
Continually monitor data collection.
Develop methodologies to improve data analysis.
Perform analysis of HAL data system as needed, which may include reviewing documentation and analyzing current HAL system/ environment, including data models, schemas and tables, data dictionaries, ETL’s, system and database management processes, data quality, security, queries, reporting environment.
Work with OHA project team members (PM, BAs, DBAs, data analysts, architects), HAL management and HAL users to identify/ determine business/technical requirements.
Gather and document detailed system, data and integration requirements for HAL system improvements (e.g. changes to ETL code, business rules, HAL tables, new or updated OHG Medicaid claim code grouping categories, etc.)
Design, develop and implement data pipelines using ETL processes and SQL tables that extract, transform, and load data into a HAL Medicaid data system/ datamart that helps the organization reach its strategic goals.
Migrate existing ETL process built in legacy SAS coding to Microsoft Structured Query Language (“SQL”) stack and Python language/ stored procedures, by: Working with various program areas and business teams to make code as modular as possible. Reviewing and analyzing existing ETL SAS programming code to update to new SQL/ Python language/ procedures Developing new SQL stack / stored procedures programming code to create new ETL processes.
Test, troubleshoot and implement the new ETL code in the HAL test and production environments.