Data Solutions Engineer

The Data Solutions Engineer is responsible for building, managing, and optimizing data pipelines to support business initiatives.

RESPONSIBILITY LEVEL:

The Data Solutions Engineer is responsible for building, managing, and optimizing data pipelines to support business initiatives.

This role oversees moving pipelines into production, ensures compliance with data governance and security standards, and enables integrated, reusable data processes.

As a central resource, the data engineer works with IT and business units to deliver analytics and data science solutions, requiring innovation, problem-solving, and collaboration.

The role also promotes effective data management practices and improves understanding of data and analytics.

Success is measured by how well data capabilities are integrated and aligned with business outcomes.

Implements organization s goals, may provide input into strategic goals for IT.

Conducts research, evaluates data, and reports on findings, supporting the development and implementation of policies, procedures, and programs.

Has familiarity with the IT budget, may provide input into spending decisions, particularly as pertains to vendors, systems, and projects.

Typically works on projects and initiatives that span 12 months 2 years.

PRINCIPAL DUTIES:

1.

Oversee the operations pertaining to all aspects of data pipelines including the creation, maintenance and optimization of organization data capabilities and demands.

2.

Optimize existing ETL processes, data integration, and data pipeline flows.

Perform advanced troubleshooting, root cause analysis, and resolution of integration or data integrity issues.

Provide production support including analysis, design, implementation and testing.

3.

Support enterprise data initiatives such as data warehouses, AI workflows, and reporting needs by enabling governed, reliable data that drives business decisions and maximizes the value of data as a strategic asset.

4.

Oversee data governance, data quality, and security standards for new and existing data pipelines while directing the design and documentation of data mappings, interface specifications, and system dependencies; lead testing, validation, and deployment of integration solutions across environments, and ensure effective knowledge transfer to internal teams.

5.

Develop relationships with stakeholders and subject matter experts across the organization to enhance requirements for various data initiatives and consumption needs.

6.

Promote the available data resources and expertise to business unit leaders to educate around the benefits in leveraging data, as an asset, to achieving their business goals.

7.

Leverage modern tools, techniques, and architectures to automate common, repetitive, and tedious data tasks to minimize manual and error-prone processes and increase productivity.

8.

Project and Change Management: Effectively plans and manages own work to reliably complete routine job responsibilities and special a...