More jobs:
Data Engineering - Lead
Job in
Charleston, Charleston County, South Carolina, 29401, USA
Listed on 2026-07-24
Listing for:
Pyramid Consulting
Full Time
position Listed on 2026-07-24
Job specializations:
-
IT/Tech
Data Engineering, Data Warehousing
Job Description & How to Apply Below
Data Engineering
- Lead
Immediate need for a talented Data Engineering
- Lead. This is a fulltime opportunity with long-term potential and is located in Charleston, SC (Onsite).
Job
-22310 Pay Range: $130000 - $150000/annum. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location).
- Data Strategy & Architecture
- Define and drive the enterprise data engineering strategy and roadmap.
- Design scalable data architectures supporting operational, analytical, and AI workloads.
- Establish standards for data modeling, data integration, metadata management, and data lifecycle management.
- Lead modernization efforts from legacy data environments to cloud-native data platforms.
- Ensure alignment with enterprise architecture, cybersecurity, and compliance requirements.
- Data Platform Engineering
- Lead the design and implementation of enterprise data platforms utilizing cloud technologies and modern data architectures.
- Develop and maintain high-volume batch, streaming, and event-driven data pipelines.
- Build and manage data lakes, data warehouses, lakehouse architectures, and data products.
- Establish reusable frameworks and accelerators that improve engineering velocity and solution consistency.
- Drive platform automation through Infrastructure-as-Code and Data Ops practices.
- Leadership & Team Development
- Lead and mentor a team of Data Engineers, Data Architects, and Data Integration specialists.
- Establish engineering best practices and technical standards.
- Provide technical oversight, architecture reviews, and design guidance across projects.
- Foster a culture of innovation, accountability, continuous learning, and operational excellence.
- Support recruitment, onboarding, career development, and performance management activities.
- Data Governance & Quality
- Implement enterprise data governance practices.
- Establish data quality frameworks, monitoring, observability, and remediation processes.
- Partner with data stewards and business stakeholders to improve trust in enterprise data assets.
- Ensure compliance with regulatory, privacy, retention, and security requirements.
- Define and monitor KPIs related to data quality, availability, and reliability.
- AI & Advanced Analytics Enablement
- Build and optimize data environments that support AI, machine learning, and advanced analytics initiatives.
- Collaborate with data scientists and AI teams to operationalize models and data products.
- Support enterprise AI initiatives through governed, trusted, high-quality data pipelines.
- Establish patterns for feature engineering, model data preparation, and data consumption.
- Delivery & Execution
- Manage delivery of multiple concurrent data engineering initiatives.
- Create project plans, estimates, resource forecasts, and delivery commitments.
- Drive agile delivery practices while maintaining governance and quality expectations.
- Identify risks, dependencies, technical debt, and remediation plans.
- Ensure predictable delivery, operational stability, and stakeholder satisfaction.
- Stakeholder Engagement
- Work closely with executive leadership to align data investments with business objectives.
- Partner with engineering, product management, operations, and business teams to prioritize initiatives.
- Present technical recommendations, investment strategies, and progress updates to leadership audiences.
- Act as a trusted advisor for enterprise data strategy and modernization initiatives.
Experience:
- Must have skills: Data Architecture, Data Governance, Insurance
- Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or related field.
- Master's degree preferred.
- 10+ years of experience in Data Engineering, Data Architecture, or related technology disciplines.
- 3+ years leading technical teams or enterprise-scale data initiatives.
- Demonstrated experience designing and delivering enterprise data platforms.
- Experience leading cross-functional teams in global delivery environments.
- Technical Expertise
- Strong experience in multiple areas including:
- SQL and advanced database technologies
- Python, Spark, Scala, or similar data engineering technologies
- ETL and ELT frameworks
- Data Lakes, Lakehouse, and Data Warehouse architectures
- Cloud platforms (Azure, AWS, or Google Cloud)
- Databricks, Snowflake, Synapse, Redshift, Big Query, or equivalent technologies
- Real-time data processing and streaming architectures
- API-based integration and event-driven architectures
- CI/CD, Data Ops, Infrastructure-as-Code, and automation practices
- Insurance industry experience.
- Experience supporting AI, Machine Learning, and Generative AI initiatives.
- Experience implementing enterprise data governance programs.
- Success leading large-scale cloud migration or data modernization programs.
- Experience with observability, operational monitoring, and reliability engineering.
- Leadership Competencies
- Strategic Thinking
- Technical Leadership
- Decision Making
- Stakeholder Management
- Talent Development
- Executive…
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