via Indeed
$140K - 165K a year
Design, build, and lead cloud-native data platform architecture and pipelines, ensuring data quality, governance, and performance optimization while mentoring a team of data engineers.
12+ years data engineering experience with 3+ years lead role, strong cloud platform expertise, hands-on with Python, SQL, Databricks, Spark, modern data warehouse technologies, and leadership skills.
Job Description We are building a next-generation Cloud Data Platform to unify data from Policy, Claims, Billing, and Administration systems into a single source of truth. We are seeking a Lead Cloud Data Engineer who will be 75% hand-on and play a critical role in designing, building, and optimizing our modern data ecosystem leveraging Medallion architecture, Delta Lake, and modern data warehouse technologies such as Snowflake, Synapse, or Redshift. As a technical leader, the Lead Data Engineer will define and execute the end-to-end data engineering strategy from data ingestion and modeling to governance and performance optimization enabling scalable, high-quality, and analytics-ready data assets. This role requires hands on deep technical expertise in cloud-native data engineering, automation, and architecture design, coupled with strong leadership to mentor teams and align solutions with business goals. Responsibilities Data Platform Design & Architecture • Define the strategic roadmap for the enterprise data platform, ensuring scalability, performance, and interoperability across business domains. • Architect and implement cloud-native, Medallion-based data architectures (Bronze–Silver–Gold layers) for unified and governed data delivery. • Drive standardization of data models, pipelines, and quality frameworks across Policy, Claims, Billing, and Administrative data assets. • Evaluate and implement emerging data technologies to strengthen the platform’s performance, cost efficiency, and resilience Data Integration & Ingestion • Design, build, and optimize high-performance ingestion pipelines, using AWS Glue, Databricks, or custom Spark applications. • Automate ingestion of structured, semi-structured, and unstructured data from APIs databases, and external data feeds. • Tune and monitor ingestion pipelines for throughput, cost control, and reliability across dev/test/prod environments. Data Transformation & Modeling • Hands on Development of ETL/ELT pipelines using Databricks or similar frameworks to transform raw data into curated and consumption-ready datasets. • Design and develop relational, Vault, and dimensional data models to support analytics, BI, and AI/ML workloads. • Define and enforce data quality standards, validation frameworks, and enrichment rules to ensure trusted business data. • Apply data quality, cleansing, and enrichment logic to ensure accuracy and completeness of business-critical data. Cloud Infrastructure, Automation and Performance • Collaborate with DevOps and Cloud Engineering teams to design automated, infrastructure-as-code environments using Terraform, CloudFormation, or equivalent tools. • Implement CI/CD pipelines for data pipeline deployment, versioning, and testing. • Lead performance tuning and scalability optimization to ensure highly available, cost-efficient data platform. Governance, Security & Compliance • Implement and enforce data governance, cataloging, and lineage practices using tools such as Purview, Alation, or Collibra. • Partner with InfoSec to implement data privacy, access control, and compliance frameworks aligned with regulatory standards. • Drive consistency and accountability in data stewardship across business and IT teams. Leadership, Collaboration & Mentorship • Lead a team of data engineers, providing technical guidance, coaching, and performance mentorship. • Collaborate with Data Architects, Analysts, and Business Leaders to align data solutions with enterprise strategy. • Promote a culture of engineering excellence, reusability, and knowledge sharing across data organization. • Influence enterprise-wide standards for data engineering, automation, and governance. Skills/Requirements Qualifications: • Bachelor’s or master’s degree in computer science, Data Engineering, or a related field. • 12+ years of experience in data engineering with at 3+ years in a lead or architect-level role and least 8+ years on cloud platforms (AWS, Azure, or GCP). • Deep hands-on experience with Python, SQL, and data modeling (relational, and Dimensional), Databricks, Spark, AWS Glue, Delta Lake, Snowflake, Synapse, or Redshift • Proven experience with Medallion architecture, modern data warehousing principles., data governance, lineage, and CI/CD for data pipelines • Excellent leadership, communication, and cross-functional collaboration skills. • Experience in the Property & Casualty (P&C) Insurance domain such as Policy, Claims, or Billing data preferred. • Familiarity with event-driven architectures (Kafka, Kinesis) and real-time data streaming. • Knowledge of machine learning pipeline integration and feature engineering. • Proven ability to lead large-scale data modernization or cloud migration initiatives. Compensation • $140,000 - $165,000 commensurate with experience, plus bonus eligibility Benefits We are proud to offer a robust benefits suite that includes: • Competitive base salary plus incentive plans for eligible team members • 401(K) retirement plan that includes a company match of up to 6% of your eligible salary • Free basic life and AD&D, long-term disability and short-term disability insurance • Medical, dental and vision plans to meet your unique healthcare needs • Wellness incentives • Generous time off program that includes personal, holiday and volunteer paid time off • Flexible work schedules and hybrid/remote options for eligible positions • Educational assistance #TMG
This job posting was last updated on 12/5/2025