Senior Data Engineer at Great Day Improvements

Twinsburg, Ohio, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Jun, 26

Salary

160000.0

Posted On

21 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Databricks Lakehouse, Unity Catalog, Delta Live Tables, SQL, Python, RDBMS, NoSQL, ETL, Data Governance, Data Architecture, Metadata-Driven Development, Data Modeling, Data Quality, MDM, Structured Streaming, Change Data Capture

Industry

Construction

Description

Overview Great Day Improvements - Senior Data Engineer (Twinsburg, OH / Hybrid) Since its founding 13 years ago, Great Day Improvements, LLC has grown rapidly toward its vision of becoming one of the largest home improvement companies in the U.S. Headquartered in Twinsburg, Ohio, Great Day Improvements is a $1.5 billion, vertically integrated, direct-to-consumer provider of premium home improvement products. The company’s family of brands includes Patio Enclosures®, Champion Windows and Home Exteriors®, Universal Windows Direct®, Apex Energy Solutions®, Stanek Windows®, Leafguard®, Englert®, and The Bath Authority. With an expanding workforce of over 4,800 employees across 130 metropolitan markets throughout the U.S., Great Day Improvements continues to rank among the top home improvement companies nationwide and is one of the fastest growing private companies in America. Job Summary The Senior Data Engineer spearheads digital transformation initiatives at Great Day Improvements, liaising with system architects and integrating data from various sources. This role is centered on the Databricks Lakehouse platform and requires deep expertise in Unity Catalog for data governance and access control, Delta Live Tables (DLT) for pipeline orchestration, and metadata-driven development patterns that maximize reuse, configurability, and maintainability across the data estate. The ideal candidate will have proven experience in constructing and managing RDBMS and NoSQL ETL, migrations, and data management, with a focus on developing optimized data architecture. The Senior Data Engineer provides critical support to software developers, data analysts, and data scientists in data-related initiatives, ensuring that the architecture for data delivery is maintained optimally throughout all ongoing projects. This role requires an individual who is self-motivated, embraces AI-assisted development workflows, and is adept at addressing the data needs of multiple teams, systems, and products. The ideal candidate will be enthusiastic about contributing to the design and enhancement of the data infrastructure to support the continuous growth of Great Day’s portfolio of brands. Location: Twinsburg, OH (Hybrid) Pay: $160,000 per year Responsibilities Data Pipeline Design & Development Design, develop, and maintain scalable and reliable data pipelines that integrate data from multiple sources (CRM, ERP, etc.) into a cohesive data ecosystem Collaborate with stakeholders to understand data requirements and deliver comprehensive data models that support business needs Build processes supporting data transformation, data structures, metadata, dependency, and workload management Architecture & Standards Analyze and improve existing data architectures to enhance performance and scalability within the Databricks Lakehouse platform Build and maintain metadata-driven pipeline frameworks that use external configuration (tables, JSON, YAML) to control pipeline behavior, schema mappings, transformations, and data flow—minimizing hardcoded logic and maximizing reusability Contribute to developing and documenting internal and external standards for pipeline configurations, naming conventions, partitioning strategies, and more Stay abreast of industry trends and technologies to drive innovation within the data management space Data Governance & Quality Develop and enforce data governance policies and procedures to ensure data integrity and security Configure and maintain Unity Catalog securable (catalogs, schemas, tables, volumes) with appropriate grants and privilege hierarchies to enforce least-privilege access Ensure high operational efficiency and quality of data platform datasets for project reliability and accuracy through DLT expectations, data quality checks, and monitoring Implement and manage Master Data Management (MDM) strategies and solutions to ensure data accuracy, completeness, and consistency across the organization Leverage Unity Catalog’s data lineage and audit logging capabilities to support compliance, impact analysis, and operational transparency Qualifications Required 5+ years of experience in a data engineer role, with a graduate degree in computer science, statistics, informatics, information systems, or another quantitative field Proven experience in data engineering, data integration, and data architecture Strong proficiency in SQL and experience with relational and NoSQL databases Advanced working SQL knowledge including query authoring and familiarity with various databases (MS SQL, PostgreSQL, MySQL, Oracle, etc.) Experience building and optimizing big data pipelines, architectures, and data sets A successful history of manipulating, processing, and extracting value from large, disconnected datasets Skills in one or more languages such as SQL (Required), Python, C#, Java, Kotlin, Scala, R, and JavaScript Excellent problem-solving, analytical, and communication skills Preferred 3+ years of hands-on experience with the Databricks Lakehouse platform, including Delta Lake, DLT pipelines, and the Databricks SQL and notebook environments Experience implementing Unity Catalog across multiple workspaces with centralized governance patterns Proven track record building parameterized, config-driven DLT pipelines that can onboard new data sources with minimal code changes Experience with Databricks Auto Loader, Structured Streaming, and Change Data Capture (CDC) patterns Experience with CRM and ERP systems integration Knowledge of index optimization, data replication/clustering, and archive strategies Experience with SQL Server linked servers, triggers, constraints, synonyms, views, UDFs, and stored procedures Experience with scheduling and process execution tools such as SQLCMD, BCP, DTExec, mysqldump, mongodump, mongosh, bash, PowerShell, and Python Experience documenting complex data architecture in GitHub Flavored Markdown Understanding of data concepts including CRDT, event sourcing, and the “Big Vs” of data in a polyglot hybrid cloud environment Competencies Strong analytical skills related to working with structured and unstructured datasets Ability to quickly understand complex systems and data flows Problem-solving orientation and technical communication Self-motivated with ability to address data needs across multiple teams, systems, and products Passion for data infrastructure design, metadata-driven development patterns, and continuous improvement Enthusiasm for leveraging AI tools and assistants to enhance engineering productivity and code quality Success Measures Success in this role will be measured by: Data pipelines are reliable, performant, and deliver data on time to downstream consumers Data architecture supports current and future business needs with minimal rework Metadata-driven frameworks are adopted and new data source onboarding requires configuration changes rather than new pipeline code Data governance standards are documented, enforced, and adopted across the organization Data quality issues are identified proactively through DLT expectations and monitoring, and resolved efficiently Cross-functional teams (analysts, data scientists, developers) are effectively supported with quality data MDM strategies are implemented and drive consistency across the organization GDI is an Equal Employment Opportunity Employer

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Responsibilities

The Senior Data Engineer will design, develop, and maintain scalable data pipelines integrating data from multiple sources into a cohesive ecosystem, while also analyzing and improving existing data architectures within the Databricks Lakehouse platform.