Data & AI Engineer

Location: Remote, FL

Our Company

• Explore how you can contribute at AmeriLife.
• For over 50 years, AmeriLife has been a leader in the development, marketing and distribution of annuity, life and health insurance solutions for those planning for and living in retirement.
• Associates get satisfaction from knowing they provide agents, marketers and carrier partners the support needed to succeed in a rapidly evolving industry.

Job Summary

AmeriLife is seeking a Data & AI Engineer to help build, modernize, and scale our enterprise data and artificial intelligence capabilities.

Reporting to the Director of Data Engineering within the Enterprise Data & AI Platforms organization, this individual will play a hands-on engineering role in developing modern data pipelines, integrating enterprise data sources, and driving intelligent automation across the organization.

The role will focus on advancing AmeriLife's Databricks Lakehouse platform, supporting the transition from legacy data environments to scalable, cloud-native architectures, and enabling enterprise analytics, reporting, and automation.

This is a hands-on engineering position requiring exceptional proficiency in Python, PySpark, and SQL, a strong foundation in modern data engineering, and a hyperautomation mindset focused on eliminating manual processes, building reusable engineering frameworks, and improving operational efficiency.

The ideal candidate is a technically curious, execution-oriented engineer who enjoys writing code, solving complex problems, and applying modern technologies to build scalable, automated enterprise data solutions.

Key Responsibilities

Enterprise Data Engineering & Databricks

Design, develop, test, and maintain scalable data ingestion, transformation, and integration pipelines using Databricks, PySpark, Python, and SQL.

Build and enhance enterprise data pipelines following modern Lakehouse and Medallion Architecture (Bronze, Silver, and Gold) principles.

Develop reusable, modular, and metadata-driven ETL/ELT frameworks to support enterprise data processing.

Ingest and integrate structured and semi-structured data from databases, APIs, flat files, cloud storage, and enterprise applications.

Work with Delta Lake, Unity Catalog, Databricks Workflows, and related platform capabilities.

Support migration and modernization of legacy SQL Server, SSIS, and traditional data warehouse workloads onto Databricks.

Optimize data pipelines and transformations for performance, reliability, scalability, and cost efficiency.

Apply advanced Python, PySpark, and SQL techniques to solve complex data processing and engineering challenges.

Collaborate with senior engineers and architects to implement enterprise data engineering standards and best practices.

Additional Locations: Remote, MT, Remote, MI, Remote, MA, Remote, RI, Remote, WV, Remote, OR, Remote, OK, Remote, MN, Remote, NY, Remote, SC, Remote, KY, Remote, VA, Remote, CO, Remote, NJ, Remote, WI, Remote, UT, Remote, PA, Remote, OH, Remote, NC, Remote, NE, Remote, MS, Remote, SD, Remote, MD, Remote, LA, Remote, KS, Remote, IA, Remote, IL, Remote, TN, Remote, DE, Remote, CT, Remote, CA, Remote, HI, Remote, AR, Remote, DC, Remote, GA, Remote, MO, Remote, AZ, Remote, AL, Remote, NH, Remote, TX, Remote, VT, Remote, IN, Remote, WA, Remote, NV, Remote, ID, Remote, NM, Remote, ME