Senior Data Engineer

Role Overview

• Provide technical leadership to data engineers, setting standards for solution design, coding practices, data governance, and quality.
• Define and evolve the enterprise data architecture leveraging Snowflake, Data Vault 2.0, and modern event driven and ELT frameworks.
• Lead architecture reviews, establish engineering best practices, and guide platform modernization efforts.
• Mentor engineering team members, facilitate code reviews, and promote continuous learning and innovation.
• Architect and oversee the delivery of scalable data pipelines, ingestion frameworks, and transformation processes using Snowflake, Python, Spark, Informatica (PowerCenter/IDMC), AWS Glue, and cloud-native tooling.
• Design and maintain enterprise data models, including Data Vault 2.0 (Hubs, Links, Satellites, PIT, Bridge structures) and dimensional models.
• Develop and optimize Snowflake platform capabilities, including: Snowpipe, Streams, Tasks, File Formats, External Stages Dynamic Tables and ELT pipeline automation.
• Warehouse sizing, performance tuning, and cost optimization.
• Implement scalable batch, micro-batch, and real-time ingestion solutions following best practices.
• Translate complex business requirements into technical design specifications and actionable development plans.
• Partner with product owners, business stakeholders, architects, and analytics teams to deliver high-impact data solutions.
• Manage technical execution across multiple initiatives, ensuring alignment with enterprise priorities, data strategies, and delivery timelines.
• Oversee documentation, deployment readiness, testing processes, and quality assurance for production releases.
• Ensure operational reliability, data accuracy, and performance of enterprise data warehouse and analytical environments.
• Lead root-cause analysis for production issues and drive implementation of long-term preventative solutions.
• Conduct performance optimization on Snowflake workloads, SQL queries, pipelines, and integrations.

Requirements

• 8+ years of experience in data engineering, with 2+ years in a senior, lead, or architect capacity.
• Advanced hands-on expertise in Snowflake, including constant learning on advanced new features.
• Strong experience implementing Data Vault 2.0 models and automated ELT frameworks.
• Proficiency with ETL/ELT and data integration tools such as Informatica IDMC, PowerCenter, Pentaho, AWS Glue, Control M and Python-based pipelines.
• Deep understanding of:
• Data warehousing and analytics engineering principles
• Dimensional modeling and relational structures
• ELT patterns, CDC frameworks, and metadata-driven design
• Orchestration frameworks (Control-M, Airflow)
• Strong SQL expertise with experience in stored procedures, Snowflake Scripting, and complex query optimization.
• Hands-on experience designing and delivering large-scale AWS-based data platforms.
• Demonstrated leadership in guiding teams, influencing architecture decisions, and managing technical delivery.
• Excellent communication and collaboration skills with the ability to partner across technical and business teams.

Tech Stack

• Airflow
• AWS
• Cloud
• ETL
• Informatica
• Python
• Spark
• SQL
• Vault

Benefits

• Qualify for your choice of health and dental plans within your first month.
• Save for your future with robust 401(k) match, Health Spending Accounts and various retirement plans.
• Learn and Grow with our Tuition Assistance Program, paid certifications and continuing education programs.
• Contribute to your community through United Way and volunteer programs.
• Balance your life with generous paid time off and business casual dress.
• Get employee discounts for shopping, dining and travel through Kemper Perks.