Senior Data Engineer

Delta Dental•Alpharetta, GA

9d•Onsite

About The Position

Delta Dental Insurance Company is seeking a Senior Data Engineer to design, develop, and implement enterprise data engineering solutions. This role involves collaborating with various teams to translate business requirements into scalable data models, cloud data pipelines, and integration frameworks. The engineer will build and optimize data processing platforms using Microsoft Azure services, design end-to-end ETL/ELT pipelines, and create complex SQL logic. Responsibilities also include developing and maintaining data warehouse and data lake architecture, performing data profiling and quality checks, prototyping solution designs, and designing dashboards and visualizations using Power BI. Automation using Python and Unix Shell scripting, troubleshooting data pipeline issues, and participating in data architecture discussions are key aspects of this role. The position requires preparing technical design documents, supporting all phases of the Software Development Lifecycle (SDLC), and mentoring junior team members. The role is located in Alpharetta, GA, and requires the candidate to live within a reasonable commuting distance from HQ and be able to appear in the 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 the job offered or related ETL Development/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 applying performance tuning techniques.
Building ETL and data integration workflows using SAP Data Services, SSIS, and Azure Data Factory (ADF), 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.

Responsibilities

Design, develop, and implement enterprise data engineering solutions to support business processes and analytical requirements.
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 (ADF) to extract, transform, and load structured and unstructured 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 to support operational and analytical workloads.
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 all designs follow organizational and security standards.
Support all phases of the Software Development Lifecycle (SDLC), including requirements analysis, technical design, development, testing (unit, integration, system), deployment, and production support.
Mentor junior team members by providing guidance on best practices, coding standards, and cloud data engineering methodologies.