Data Analyst-Data Modeler/Engineer-ETL-Source-to-Target Mapping

American IT Systems•Minnetonka, MN

5d•Hybrid

About The Position

This role is for a Data Analyst-Data Modeler/Engineer with expertise in ETL and Source-to-Target Mapping. The position is located in Minnetonka, MN, and is a hybrid role requiring 3 days in the office. This is a contract position expected to last 8-12 months. Only local candidates are accepted. The role involves designing and implementing scalable data pipelines and storage solutions, ensuring data quality, integrity, and security. It requires collaboration with stakeholders to define data requirements and translate them into technical specifications. The position also involves monitoring and optimizing data systems and ETL processes, supporting data infrastructure in cloud environments, and developing complex SQL scripts. A key aspect is leveraging Informatica IDMC for data integration, quality, and governance. Additionally, the role includes performing exploratory data analysis, creating dashboards, automating workflows, supporting business intelligence, and applying AI/ML techniques for advanced analytics.

Requirements

Data Engineering
ETL
Informatica
SQL/Oracle PL-SQL
Informatica PowerCenter
Data Modeling
Data Analysis
Snowflake or Azure or Kafka – Preferred
Healthcare Insurance

Nice To Haves

Snowflake
Azure
Kafka
Python
R
Power BI
Tableau
Excel
TensorFlow
Azure Machine Learning
scikit-learn
PyTorch

Responsibilities

Designing and implementing scalable data pipelines and storage solutions to support enterprise analytics.
Ensuring data quality, integrity, and security across all stages of the data lifecycle.
Collaborating with stakeholders to define data requirements and translate them into technical specifications.
Monitoring and optimizing performance of data systems and ETL processes.
Supporting the deployment and maintenance of data infrastructure in cloud environments.
Developing and maintaining complex SQL scripts and stored procedures for data transformation and reporting.
Leveraging Informatica IDMC for cloud-native data integration, data quality, and governance workflows.
Performing exploratory data analysis and generating actionable insights.
Creating dashboards and visualizations using tools like Power BI, Tableau, or Excel.
Collaborating with cross-functional teams to align data efforts with business goals.
Automating data workflows using scripting languages such as Python or R.
Supporting business intelligence initiatives and translating data into strategic recommendations.
Documenting data processes and contributing to data governance standards.
Applying AI and machine learning techniques to enhance predictive analytics, automate decision-making, and uncover deeper insights from complex datasets.
Utilizing preferred AI tools and platforms such as TensorFlow, Azure Machine Learning, scikit-learn, and PyTorch to build and deploy models that support enterprise analytics and innovation.