Data Engineer

The Data Engineer is responsible for designing, building, and maintaining scalable, reliable data ingestion and delivery systems that support analytics, reporting, and business decision-making across Heartland. This role plays a key part in the evolution and operation of the BI and enterprise data warehouse (EDW) environment, ensuring data is accessible, trusted, and available in formats that meet business needs. The Data Engineer partners closely with data owners, business leaders, application teams, and analytics stakeholders to define data standards, optimize data architecture, and continuously improve data platform performance, reliability, and usability. KEY RESPONSIBILITIES Strategy & Planning Design, develop, and deploy data ingestion and egress solutions to meet evolving business and analytics requirements. Participate in defining data standards, governance practices, and warehouse architecture models. Partner with data owners and department leaders to design data models and establish protocols for accessing and analyzing production data. Contribute to the development and refinement of data management policies, procedures, and best practices. Identify gaps and improvement opportunities within data engineering processes and platforms, and communicate recommendations to stakeholders. Analyze existing BI and EDW architecture and recommend enhancements to support scalability, performance, and growth. Establish and support best practices for operating in a high-availability, 24/7, global data environment. Data Engineering & Platform Operations Build, maintain, and optimize data pipelines, transformations, and data models. Collaborate with application development teams to design and manage data queries, procedures, and integrations. Monitor data warehouse performance, including stored procedures and query execution, and implement efficiency improvements. Diagnose and resolve data access, quality, and performance issues across the data platform. Develop and maintain change control, testing, and deployment processes for data model and pipeline changes. Data Quality, Enablement & Collaboration Implement and promote data quality, validation, and monitoring practices. Define and maintain data definitions and metadata for new and existing database objects. Collaborate with business users, analytics teams, and IT partners to ensure data solutions align with business needs. Create documentation, standards, and reusable routines to enable best-practice use of data tools. Provide guidance and support to data consumers to improve data literacy and effective data usage. QUALIFICATIONS Education & Experience Bachelor's degree in Information Technology, Computer Science, or a related field Proven experience delivering data engineering, data warehousing, or business intelligence solutions Experience integrating data across multiple systems and platforms with a focus on reuse and scalability Ability to manage multiple priorities and work independently as well as collaboratively in a team environment Knowledge & Technical Skills Strong knowledge of data warehousing methodologies, data modeling, data quality, and data governance Advanced SQL skills and experience with data manipulation and transformation Experience with Microsoft BI and data technologies Strong understanding of relational database concepts, structures, and best practices Hands-on experience with large-scale data modeling, data mining, and business requirements analysis Experience working in a DevOps or agile environment, including version control (e.g., Git), code reviews, and CI/CD practices Familiarity with data processing flowcharting and documentation techniques PERSONAL ATTRIBUTES Excellent written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences Strong collaboration skills and a customer-oriented mindset when working with business users Analytical, detail-oriented problem solver with strong critical-thinking skills Self-motivated, accountable, and able to operate with integrity in a fast-paced environment Proven ability to prioritize and deliver results under pressure PHYSICAL DEMANDS Ability to sit or stand for extended periods while working with computers and other electronic media Occasional overtime may be required to meet project deadlines