Senior Data Engineer

Radwell International • Willingboro Township, NJ

12d • $140,000 - $170,000 • Onsite

About The Position

As a Senior Data Engineer at Radwell, you will be a key member of the data engineering team, responsible for designing, building, and maintaining our data environment. You will collaborate closely with fellow data engineers, ML teams, reporting analysts, and software engineers to ensure our data pipelines are efficient, scalable, and reliable. The Radwell Data Engineer is a forward-thinking innovator who understands how to implement data solutions for next-generation challenges by working directly with the business to understand their data needs. Your work will help optimize activities across multiple functions such as pricing, warehousing, and procurement, driving data-driven decisions and operational efficiency throughout the organization.

Requirements

• Minimum 10 years’ experience delivering data engineering solutions on a cloud platform
• Minimum 10 years’ experience implementing modern designs using at least one cloud-based solution
• Minimum 10 years’ experience with SQL or NoSQL databases
• Minimum 10 years’ experience with at least one programming language, with a strong preference towards Python
• Advanced level proficiency with at least one ETL / data orchestration technology such as Azure Data Factory, SSIS, Informatica
• Experience in cloud-based data warehousing and data lake solutions such as Databricks, Snowflake, or Redshift
• Expertise with SQL, database design and data structures (star/snowflake schemas, de/normalized design)
• Familiarity with DevOps tools such as git, TFS, CI/CD, Jira
• Fundamental understanding of big data, open source, and data streaming concepts
• Fundamental understanding of implementation of MLOps best practices
• Familiarity with packaged software data extraction from systems such as NetSuite, Profit21 ERP as well as Salesforce CRM.
• Experience sub-setting data into cube structures for business use in data reporting and analytics.
• Ability to think strategically and provide recommendations utilizing traditional and modern architectural components based on business needs
• Excellent written and verbal communication skills along with strong desire to work in cross functional teams. Ability to present extremely complex technical information in a business-friendly manner
• A passion for staying up to date with the latest trends and advancements in the field
• Team player who can coach and be coached as needed. Openness to adapting your approach for the betterment of the team
• Strong technical ability and eagerness to learn new technologies and skills
• Attitude to thrive in an entrepreneurial, fast-paced environment
• Minimum 10 years’ experience in an analytics or data engineering role.

Responsibilities

• Architect and scale data platforms — design and maintain distributed data systems (batch + streaming), ensuring reliability, performance, and cost efficiency
• Lead end‑to‑end data pipeline development — build, optimize, and monitor ETL/ELT pipelines that support analytics, ML training, and real‑time inference workloads
• Enable machine learning workflows — collaborate with data scientists to deliver feature pipelines, model training environments, and production inference systems
• Own data quality and governance — define standards for data validation, lineage, cataloging, and compliance across the organization
• Partner with cross‑functional teams — work with product, analytics, and ML teams to translate business needs into scalable data solutions
• Operational excellence — manage CI/CD for data and ML pipelines, implement observability, and ensure SLAs for mission‑critical data services
• Evaluate and integrate new technologies — assess tools for data processing, orchestration, storage, and MLOps; lead POCs and production rollouts
• Build and maintain advanced data systems that bring together data from disparate sources in order to enable decision makers
• Design, develop, and maintain scalable data pipelines and ETL processes using Databrick, azure data factory, SQL and Python
• Build pipelines and prepare data for use by data scientists, data analysts, and other data systems
• Take a solution-oriented problem-solving approach to develop creative solutions for business needs by partnering with business leaders and subject matter experts
• Leverage cloud infrastructure and metadata driven frameworks to deliver value and scalability
• Incorporate AI-powered developer tools (e.g., GitHub Copilot, Cursor, Claude Code) to accelerate code scaffolding, boilerplates, and refactoring
• Govern the deployment pipeline by maintaining ultimate accountability for the security, extensibility, and clarity of AI-generated code
• Automate test suites using Generative AI to programmatically generate edge-case validation checks, regression testing, and data quality rules.
• Manage continuous integration and zero-touch deployment (CI/CD) via GitHub Actions, Terraform, or Jenkins, using AI to debug execution failures and draft deployment manifests
• Implement rollback strategies and reversible migration practices for schema modifications developed through automated workflows
• Build automated anomaly detection and schema drift monitoring alerts into critical business pipelines
• Enforce data governance standards, maintaining clear lineage tracking and access controls across cloud layers

Benefits

• health, dental, and vision coverage
• company sponsored short-term and long-term disability benefits
• $50,000 in Life insurance
• voluntary benefits
• 401(k) Plan
• common paid Company Holidays
• 15 days of PTO annually

What This Job Offers

• Job Type: Full-time
• Career Level: Senior