Data Engineer

Overview

Position Description

We are seeking a motivated Data Engineer to support the modernization of our our clients' insurance agency and policy admin data platforms. This role offers the opportunity to work with cloud technologies (AWS or Azure), build scalable data pipelines, and integrate key systems such as Applied Epic, Ivans, EzLynx, AL3 data integration, Guidewire, and Salesforce FSC. In this role you will contribute to real-time analytics, predictive modeling, and customer insights, while collaborating with cross-functional teams to deliver high-impact data solutions.

This is a Full Time Employment opportunity, based in Indianapolis, IN and Portsmouth, RI.

• Participate in the transition from legacy systems to modern cloud-based data platforms (e.g., AWS, Azure).
• Migrate key insurance data (policy) from Applied Epic and Guidewire into unified data warehouses/lakes for advanced analytics.
• Architect Insurance Data Ecosystem.
• Design scalable data architectures that support future-state personal lines insurance workflows, omnichannel engagement, and predictive analytics.
• Integrate Applied Epic, Guidewire, and Salesforce FSC data for 360° customer and policyholder insights.
• Prepare structured datasets for actuarial modeling, underwriting automation, and customer segmentation using ML and AI tools.
• Collaborate with data scientists to deploy models into production environments and monitor model performance over time.
• Build real-time and event-driven data pipelines to support dynamic pricing, and customer notifications.
• Leverage tools like Kafka, AWS Kinesis, or Pub/Sub for real-time processing across policyholder journeys.
• Implement automated data cataloging, lineage tracking, and access controls aligned with NAIC, GDPR, and CCPA requirements.
• Use metadata management and data observability tools to ensure future scalability, trust, and transparency.
• Enable APIs and data layers to support partnerships and embedded insurance models.
• Collaborate with third-party Insurtech platforms, MGAs, and distribution partners through secure data integrations.
• Develop reusable, curated datasets and data marts that empower underwriters, and business analysts.
• Create training content and documentation to promote self-service data usage across business units.
• Integrate Salesforce FSC with internal insurance systems to deliver hyper-personalized customer communications and retention strategies.
• Build data layers that power cross-sell/up-sell recommendations and lifecycle marketing based on claims or policy behavior.
• Adopt agile methodologies for iterative data delivery and implement CI/CD pipelines for data deployments.
• Participate in automation in testing, monitoring, and documentation of data products and pipelines.

• 3–5 years of professional experience as a Data Engineer, preferably in the insurance or financial services industry.
• Strong domain knowledge of Personal Lines Insurance (Auto, Homeowners, Renters, etc.), including policy lifecycle, Renewal, billing, and underwriting.
• Hands-on experience working with Applied Epic and Guidewire (Policy Center, Billing Center, or Claim Center).
• Familiarity with Salesforce Financial Services Cloud (FSC) or core Salesforce CRM data models (nice to have but preferred).
• Understanding Insurance data structures, workflows, and APIs specific to insurance operations and customer engagement.
• Proficient in SQL and one or more programming languages like Python, Scala, or Java for data transformation and scripting.
• Experience building ETL/ELT pipelines using tools such as dbt, Talend, Informatica, or custom frameworks.
• Working knowledge of cloud-based data platforms (e.g., AWS Glue/Redshift, Azure Data Factory/Synapse, GCP Big Query).
• Exposure to streaming and event-driven architecture (e.g., Kafka, Kinesis, Spark Streaming) is a plus.
• Ability to design and implement insurance data models across policy, claims, customer, and finance domains.
• Experience with dimensional modeling, normalization/denormalization, and building data marts for reporting/analytics.
• Knowledge of data governance best practices including data quality, lineage, access control, and metadata management.
• Famili…