Senior Data Engineer

Delta Dental is seeking a Senior Data Engineer for Alpharetta, GA on a hybrid schedule. This role offers a competitive base and incentive pay, a comprehensive benefits package, and a culture that prioritizes growth, learning, and community impact. The position carries a salary range of USD 160,056 - 165,056 per year, requires a Bachelor's degree or foreign degree equivalent, and five years of related experience with the ability to appear in the office as required.

Technologies used in this role include SAP Data Services, SSIS, Azure Data Factory, Azure SQL Database, Oracle, Microsoft SQL Server, Power BI, Python, Unix Shell scripting, ERWIN, GitHub, SVN, Jenkins, SQL Server Agent, TIDAL, SAP BODS, Star schema, and Snowflake schema.

Benefits

• Competitive base and incentive pay
• 401(k) with robust matching and non-matching contributions
• Rich medical & pharmacy benefits
• 100% employer-paid dental and vision benefits
• Holistic wellbeing program with deep financial incentives
• Generous paid time off plus 12 paid holidays and your birthday off
• Culture of growth and learning: career development; tuition reimbursement; recognition program
• Family support: adoption assistance, fertility treatment, child, elder & pet care assistance
• Social responsibility and volunteer opportunities
• Employee discount program

Responsibilities

• Design, develop, and implement enterprise data engineering solutions to support business processes and analytics.
• Collaborate with Business Analysts, Architecture teams, and cross functional stakeholders to gather requirements and translate them into scalable data models, cloud data pipelines, and integration frameworks.
• Design and implement data integration processes using SAP Data Services, SSIS, and Azure Data Factory to extract, transform, and load data across heterogeneous systems.
• Build and optimize data processing platforms using Microsoft Azure services including Azure Data Factory and Azure SQL Database.
• Design end-to-end ETL/ELT pipelines for ingestion, transformation, and analytical data preparation; create complex SQL logic, stored procedures, packages, and functions in Oracle and SQL Server.
• Develop and maintain data warehouse and data lake architecture using Star and Snowflake schema designs.
• Perform data profiling, data quality checks, and enforce governance standards to ensure integrity, consistency, and compliance across the data lifecycle.
• Prototype solution designs for review with business and architecture teams; evaluate and select optimal cloud technologies for ingestion, transformation, reporting, visualization, and analytics.
• Design and develop dashboards, KPIs, and visualizations using Power BI to support enterprise reporting needs.
• Automate manual workflows using Python and Unix Shell scripting.
• Troubleshoot data pipeline failures, optimize performance, and resolve data-related issues to minimize business disruption.
• Participate in data architecture discussions, contributing to integration strategies, cloud migration efforts, and modernization initiatives.
• Prepare technical design documents, mapping specifications, workflow diagrams, and solution architectures; ensure designs follow organizational and security standards.
• Support all phases of the Software Development Lifecycle (SDLC), including requirements analysis, technical design, development, testing, deployment, and production support.
• Mentor junior team members by providing guidance on best practices, coding standards, and cloud data engineering methodologies.
• Must live within reasonable commuting distance from HQ and able to appear in office as required.

Requirements

• Bachelor's degree or foreign degree equivalent in Computer Science, Electrical Engineering, or related field and five (5) years of progressive, post-baccalaureate experience in ETL Development or a related Data Engineering role.
• Developing and optimizing entity relationship models using ERWIN, crafting complex SQL queries, and refining them to support analytical requirements and business insights.
• Designing, developing, and optimizing enterprise database schemas in Oracle and Microsoft SQL Server, including creation of tables, views, stored procedures, indexing strategies, and performance tuning.
• Building ETL and data integration workflows using SAP Data Services, SSIS, and Azure Data Factory, including pipelines, datasets, triggers, integration runtimes, and detailed source-to-target mapping documents.
• Designing dimensional data models for OLTP and OLAP environments using Star and Snowflake schemas and applying data architecture best practices such as normalization and de normalization.
• Developing automation scripts using Python and Unix Shell Scripting to streamline data ingestion, transformation, validation, and cloud analytics processes.
• Creating and deploying interactive dashboards and reports using Power BI to provide operational and analytical visualizations.
• Enforcing data integrity, accuracy, and compliance by applying data quality checks, validation rules, and governance frameworks throughout the data lifecycle.
• Implementing data governance and data quality processes, including data profiling, reconciliation checks, error handling logic, and anomaly detection methods.
• Designing and managing scheduling and workflow automation using ADF triggers, Jenkins, SQL Server Agent, or TIDAL to orchestrate ETL and data pipeline operations.
• Using version control systems such as GitHub or SVN to manage source code, track revisions, and maintain consistency across ETL pipelines, database artifacts, and cloud resources.
• Applying experience across all phases of the Software Development Lifecycle (SDLC) including requirements gathering, technical design, development, documentation, testing, configuration management, deployment, and production support.
• Performing troubleshooting, root cause analysis, and performance optimization of SAP BODS jobs, SQL queries, ADF pipelines, and cloud-based data transformation processes.