Data Engineer - MDM (Alt Reporting)

Insight Global; Cincinnati (OH); On-site; USD 85,000 - 130,000; Full time

Job summary

Insight Global in Cincinnati seeks a Data Engineer to design scalable data pipelines, integrate data from multiple systems, and enable BI and analytics initiatives.

You will work with cloud data platforms, real-time streaming, API development, and AI-assisted development to accelerate delivery and governance, partnering with stakeholders.

Qualifications

• 5+ years of experience in Data Engineering.
• Strong experience with PostgreSQL and data pipeline development.
• Hands-on experience with Snowflake.
• Experience integrating data with enterprise systems of record.
• Proven ability to work directly with stakeholders, gather requirements, and provide strategic recommendations.
• Experience with Kafka for real-time data streaming and event-driven architectures.
• Experience building and consuming APIs.
• Experience with orchestration and transformation tools such as dbt.
• Strong understanding of Master Data Management (MDM), including data intake, cleansing, and governance processes.
• Experience with modern data pipeline and ETL/ELT tools.
• Strong SQL and data modeling experience. Experience with Generative AI technologies and AI-assisted development workflows.
• Experience using AI tools to accelerate code generation, documentation, and development productivity.
• Exposure to modern data architecture patterns supporting AI and analytics initiatives.
• Experience supporting cloud-based data platforms and advanced analytics environments.

Responsibilities

• Design, develop, and maintain scalable data pipelines supporting enterprise reporting and BI initiatives.
• Conform, transform, and prepare data for analytics, reporting, and consumption by downstream systems.
• Develop integrations between source systems and enterprise systems of record.
• Build and maintain data ingestion, cleansing, and Master Data Management (MDM) processes.
• Develop and support real-time and batch data processing solutions.
• Create and maintain technical documentation, leveraging AI tools where appropriate to improve efficiency.
• Collaborate with business stakeholders to gather requirements, identify opportunities for improvement, and recommend data solutions.
• Build and maintain APIs and data services supporting enterprise applications.
• Support data orchestration, monitoring, and optimization using modern pipeline and workflow management tools.
• Ensure data quality, integrity, and consistency across platforms and environments.

Skills

Data engineering

PostgreSQL

Data pipelines

SQL

Data modeling

Generative AI

AI-assisted development

Cloud data platforms

Analytics environments

Stakeholder collaboration

MDM

ETL/ELT

APIs

Real-time data streaming

Tools

Snowflake

Kafka

dbt

Job description

Job Description

We are seeking a Data Engineer to join a growing team focused on building and optimizing enterprise data solutions. This role will be responsible for designing and developing scalable data pipelines, integrating data from multiple systems of record, and transforming complex datasets into a structured format that supports business intelligence and analytics initiatives. The ideal candidate will partner closely with business stakeholders to understand requirements, provide recommendations, and deliver high-quality data solutions. This individual will also leverage modern AI tools to accelerate development and documentation efforts while helping establish best practices around data governance, master data management, and data integration. Experience with cloud data platforms, real-time data streaming, and API development is critical for success in this role.

Design, develop, and maintain scalable data pipelines supporting enterprise reporting and BI initiatives.

Conform, transform, and prepare data for analytics, reporting, and consumption by downstream systems.

Develop integrations between source systems and enterprise systems of record.

Build and maintain data ingestion, cleansing, and Master Data Management (MDM) processes.

Develop and support real-time and batch data processing solutions.

Create and maintain technical documentation, leveraging AI tools where appropriate to improve efficiency.

Collaborate with business stakeholders to gather requirements, identify opportunities for improvement, and recommend data solutions.

Build and maintain APIs and data services supporting enterprise applications.

Support data orchestration, monitoring, and optimization using modern pipeline and workflow management tools.

Ensure data quality, integrity, and consistency across platforms and environments.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [e-mail] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

5+ years of experience in Data Engineering.

Strong experience with PostgreSQL and data pipeline development.

Hands-on experience with Snowflake.

Experience integrating data with enterprise systems of record.

Proven ability to work directly with stakeholders, gather requirements, and provide strategic recommendations.

Experience with Kafka for real-time data streaming and event-driven architectures.

Experience building and consuming APIs.

Experience with orchestration and transformation tools such as dbt.

Strong understanding of Master Data Management (MDM), including data intake, cleansing, and governance processes.

Experience with modern data pipeline and ETL/ELT tools.

Strong SQL and data modeling experience. Experience with Generative AI technologies and AI-assisted development workflows.

Experience using AI tools to accelerate code generation, documentation, and development productivity.

Exposure to modern data architecture patterns supporting AI and analytics initiatives.

Experience supporting cloud-based data platforms and advanced analytics environments.