Staff Software Engineer

CDK Global•Austin, TX

10d•Remote

About The Position

CDK Global, LLC seeks a Staff Software Engineer to apply specialized expertise in large-scale data engineering, ETL architecture, database design, and cloud migration across Azure and AWS platforms. This role involves architecting and implementing enterprise ETL and data processing systems, designing and maintaining data models, leading the design and buildout of new ETL environments for cloud readiness, and leading cross-functional engineering efforts. The engineer will lead the ETL engineering team in migrating the full on-prem ETL environment to Azure Data Factory, coordinate delivery for core CRM processing systems, solve complex technical challenges, redesign legacy ETL pipelines, modernize legacy VB6-based systems, implement enterprise-wide data retention processes, provide architectural leadership, develop system architecture diagrams, define data integration approaches, lead the design and implementation of the Master Data Management (MDM) “Golden ID” solution, mentor engineers, provide technical direction, conduct code reviews, partner with functional leadership, collaborate with product leaders, support roadmap discussions, and support cross-functional teams with technical expertise. The role also requires maintaining compliance with CDK policies, security standards, and data governance requirements, and ensuring adherence to cloud security, IAM configuration, data encryption, retention policies, and regulatory requirements. The engineer will meet expected deliverables for cloud migration, data platform modernization, and enterprise integration projects, including migration milestones for Azure ETL, CCP cloud transition, MDM implementation, and Sunset Legacy DMS systems and DMS system modernization. This position allows for 100% telecommuting.

Requirements

Bachelor’s degree or foreign equivalent in Computer Science, Computer Engineering, or related field and 8 years of experience as a Software Developer, or related occupation.
Using Microsoft SQL Server and T-SQL to design, develop, and support relational database solutions, including creating tables, views, stored procedures, and functions, as well as writing and optimizing complex queries through indexing, execution plan analysis, and query tuning for transactional and reporting systems.
Using ETL and data integration tools such as AWS Glue, AWS Lambda, SQL Server Integration Services (SSIS) and Azure Data Factory on Microsoft Azure to extract, transform, and load data across enterprise systems, including operating data pipelines and validating data accuracy and performance in cloud environments.
Using application development technologies such as ASP.NET, C#, VB, ADO.NET and Python to build and integrate application-level data access layers with backend databases.
Using database administration tools such as SQL Server Management Studio (SSMS), SQL Server Agent, Maintenance Plans, and Azure SQL Managed Instance’s automated management features to support backup and restore operations, index maintenance, statistics updates, and routine database health monitoring.
Using application and system monitoring tools such as AppDynamics, New Relic, Logic Monitor, and Azure Monitor to observe production environments, identify performance issues, and support troubleshooting of database and application systems.
Using reporting and analytics technologies such as SQL Server Reporting Services (SSRS), SQL Server Analysis Services (SSAS), and cloud data platforms like Snowflake to build and support analytical datasets and reporting solutions for business and operational use.
Using source control and release management tools such as Git, Team Foundation Server (TFS), Azure DevOps, and Harness CI/CD to manage code versions, support continuous integration and deployment, and maintain application and database codebases.
Working with CI/CD processes and tools, including Git, Azure DevOps, Bitbucket, Liquibase (DB Deployment), Terraform, and Harness to support version control, automate deployments, and manage environment configurations across development and production systems.
Working in Agile/Scrum environments using tools such as Jira and Confluence; participating in sprint planning, backlog refinement, and team collaboration activities.
Designing data models and supporting data warehouse environments, including dimensional modeling; developing datasets and queries to support reporting and business intelligence tools such as Snowflake, Power BI or Tableau.
Designing and supporting relational and NoSQL databases, including Microsoft SQL Server, PostgreSQL, MySQL, and MongoDB, working with structured and semi structured data and supporting both transactional and analytical workloads in distributed environments.
Monitoring and troubleshooting databases and application performance using tools such as AppDynamics, New Relic, Redgate, AWS CloudWatch, SQL Profiler, and Azure Monitor; investigating issues, analyzing trends, and supporting incident resolution in production environments.

Responsibilities

Apply specialized expertise in large-scale data engineering, ETL architecture, database design, and cloud migration across Azure and AWS platforms.
Architect and implement enterprise ETL and data processing systems using Azure Data Factory, SSIS, AWS Glue, and cloud storage platforms such as Azure Data Lake and AWS S3.
Design and maintain data models, ingestion frameworks, and transformation logic supporting CRM workflows and enterprise data services.
Lead the design and buildout of new ETL environments for cloud readiness, including migration from on premise SQL Server and SSIS workloads to Azure Data Factory.
Lead cross-functional engineering efforts involving data platform teams, cloud engineering, CRM engineering, security, and infrastructure.
Lead the ETL engineering team in migrating the full on prem ETL environment to Azure Data Factory, including technical planning, dependency management, pipeline conversion, and QA validation.
Coordinate delivery for core CRM processing systems including dealer data ingestion (DMSSOR), reference data processing, customer access databases, and pod migration workflows.
Solve complex technical challenges involving large-scale data ingestion, cloud integration, ETL optimization, and legacy system modernization.
Redesign legacy ETL pipelines to operate efficiently in Azure, including conversion of SSIS packages into ADF pipelines.
Modernize multiple legacy VB6-based systems by converting logic to C# (SSIS) and decommissioning outdated components.
Implement enterprise-wide data retention, archiving, and purging processes to improve system performance and ensure compliance.
Provide architectural leadership and technical direction for cloud migration and enterprise data initiatives.
Develop system architecture diagrams, migration strategies, and cloud transition plans for ETL workloads.
Define data integration approaches for the Connected Communications Platform (CCP) migration from on prem SQL to AWS S3 and AWS Glue.
Lead design and implementation of the Master Data Management (MDM) “Golden ID” solution to provide unified customer identity across dealership platforms.
Mentor engineers and provide specialized technical guidance on cloud ETL, data modeling, SQL optimization, and cloud migration processes.
Provide technical direction on ADF pipeline development, data architecture, SQL Server and PostgreSQL optimization, and cloud transformation.
Conduct code reviews, data model reviews, and architectural evaluations.
Partner with functional leadership to influence platform modernization priorities and architectural decisions.
Collaborate with product leaders, cloud engineers, and CRM stakeholders to determine migration timelines, resource requirements, and technical prioritization.
Support roadmap discussions related to decommissioning legacy systems and migrating to DMSSOR/Gen SOR.
Support cross-functional teams with technical expertise related to cloud systems, data integration, and ETL performance.
Assist CRM engineering, infrastructure, and security teams with data flow design, cloud ingestion patterns, ADF/SSIS processing logic, and ETL optimization.
Maintain compliance with CDK policies, security standards, and data governance requirements.
Ensure adherence to cloud security, IAM configuration, data encryption, retention policies, and regulatory requirements across ETL and CRM systems.
Meet expected deliverables for cloud migration, data platform modernization, and enterprise integration projects.
Deliver migration milestones for Azure ETL, CCP cloud transition, MDM implementation, Sunset Legacy DMS systems and DMS system modernization.