Data Engineer Sr

Job Title

Data Engineer Sr.

Position Location

Raleigh, NC.
Hybrid
Position, must live locally.

Job Summary

The Senior Data Engineer designs, builds, and optimizes modern cloudbased data infrastructure and pipelines that ensure highquality, reliable, and accessible data across the organization. This role applies strong analytical and engineering expertise to architect scalable data models, enhance data performance, and enable enterprise-wide analytics through efficient, well-governed data solutions.
Strong communication and collaboration skills enable this role to translate business needs into technical outcomes, present recommendations to leadership, influence architectural direction, mentor team members, and partner effectively with internal stakeholders and external vendors.

Responsibilities

• (30%) Deliver Scalable, HighQuality Data Pipelines
  • Architect and implement scalable, cloudnative data pipelines using Snowflake/Databricks, SQL,Python and other tools/resources that reliably deliver clean, timely, highvalue data to business and analytics stakeholders.
  • Ensure pipelines are designed for performance, observability, and longterm maintainability, enabling the organization to make confident, datadriven decisions.
  • Integrate diverse data sources into unified structures that meet stringent functional and nonfunctional requirements supporting regulatory reporting, risk analytics, fraud detection, customer insights and other banking-critical workloads.
• (20%) Elevate Data ArchitectureModeling Across Enterprise
  • Design robust relational, dimensional, and semanticlayer data models that improve data discoverability, reduce ambiguity, and enable selfservice analytics.
  • Translate complex banking business requirements-including deposits, lending, credit risk, payments, treasury, and financial crime-into robust data models, and transformation logic.
  • Improve data performance by implementing optimized schemas, indexing strategies, and modern modeling patterns that reduce query time and improve reliability.
  • Maintain a scalable Operations Data Mart that becomes a trusted, enterprisewide analytical asset.
• (15%) Advance Platform Efficiency Through Continuous Innovation
  • Identify opportunities to streamline the data ecosystem, reduce operational friction, eliminate manual workflows, and improve timetoinsight. Make recommendations for solutions and work with management to create improvement plan. Work with team members to execute changes according to the planned actions.
  • Lead proofofconcepts and research initiatives that introduce new tools, automation patterns, or architectures that modernize the data platform.
  • Establish repeatable processes that increase engineering velocity and technical consistency across the team.
• (15%) Strengthen Data Security, Governance and Compliance
  • Engineer solutions that maintain strict security controls, uphold regulatory requirements, and ensure resilience across cloud regions and data centers.
  • Embed security best practices into all data flows and access patterns, protecting sensitive information and reinforcing Coastal's standards.
  • Implement governance frameworks that safeguard data integrity, lineage clarity, and responsible usage.
• (10%) Drive Cross-Functional Outcomes Through Strategic Data Delivery
  • Translate business objectives into technical solutions that improve operational performance, member experience, and organizational insight.
  • Partner with leaders across product, analytics, and technology to design datadriven processes that scale with Coastal's growth.
  • Build and maintain strong relationships with internal and external partners to ensure seamless integration and timely delivery of enterprise data initiatives.
• (10%) Stay Current with Emerging Technologies, Industry Trends and Mentor Team
  • Continually evaluate evolving technologies, engineering standards, regulatory shifts, and cloud platform advancements to inform Coastal's data strategy.
  • Monitor new features in Data Platforms and cloud ecosystems to identify opportunities that increase efficiency, reduce cost or unlock new capabilities.
  • Champion modern best practices across the team by sharing insights, proposing improvements and influencing architectural direction.
  • Mentor team and other groups as needed in engineering best practices

Qualifications

Interested? Here are the qualifications we need to see on your resume:

Technical experience

• Five years' experience in:
  • Designing and delivering endtoend data engineering solutions using SQL, Python, and modern cloud data platforms (Snowflake, Databricks, or other ETL/ELT tools, in AWS, or Azure)