Senior Data Engineer

Jobtailor; New Jersey; On-site; USD 120,000 - 170,000; Full time

Job summary

Jobtailor in the United States, New Jersey, seeks an experienced Data Engineer Leader to drive enterprise data platforms and AI-ready assets. You will design, govern, and optimize complex data pipelines across systems, mentor engineers, and partner with product SMEs to scale data solutions for analytics and AI initiatives.

The role requires 7+ years in data engineering, advanced SQL and Python, and strong data governance expertise.

Qualifications

• 7+ years of experience in data engineering with leadership in enterprise data platforms.
• Deep understanding of data integration, governance, and analytics readiness.
• Ability to design scalable, high-performance analytics architectures.

Responsibilities

• Drive data engineering efforts to deliver enterprise-wide capabilities and complex data solutions.
• Lead data orchestration for integration, cleaning, transformation, and control across systems.
• Provide technical leadership for complex data solutions across domains.
• Mentor Data Engineers in CI/CD and best practices.
• Define ownership, lineage, governance, and quality controls for data assets.
• Build pipelines, transformations, and metadata structures for AI-ready assets.
• Define standards, guardrails, and documentation for data platforms.
• Collaborate with product SMEs to translate knowledge into reusable assets.
• Design data architecture and pipelines for data-informed decision-making.
• Oversee data governance, quality programs, and compliance requirements.

Skills

Advanced SQL Proficiency

Python Programming

Data Integration

Pipeline Development

Data Quality Frameworks

Data Modeling

Metadata Management

Large-Scale Data Processing

MLOps Practices

Data Governance Frameworks

Hybrid Data Architectures

Data Strategy Implementation

Education

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Mathematics, Statistics, or related field

Job description

• Drive data engineering efforts to deliver enterprise-wide capabilities and complex data solutions


• Direct code design and delivery for data integration, cleaning, transformation, and control across operational and analytical systems


• Work with Project Management to define outcomes and inform work structures


• Provide technical thought leadership for complex data solutions across systems and domains


• Lead design, governance, and continuous improvement of structured and unstructured data and knowledge foundations supporting AI and agentic capabilities across Network Services


• Define standards, guidelines, guardrails, and controls for documentation, configurations, telemetry, metadata, policies, standards, and operational knowledge


• Partner with product and service subject matter experts to translate network and operational knowledge into reusable AI-ready assets


• Design scalable methods for storing, governing, indexing, validating, and retrieving AI context assets


• Establish preventative and detective controls for data, metadata, knowledge, lineage, and freshness quality


• Define ownership, stewardship, lineage, freshness, governance, and control accountability


• Build or guide pipelines, transformations, validation routines, metadata structures, and supporting services


• Assemble and maintain complex data sets and processes for transformation, data structures, metadata, quality controls, dependencies, and workload management


• Design and develop data architecture using multiple architectural components


• Define and build data pipelines for data-informed decision-making


• Contribute to integration, regression, and performance test suites; analyze reports and lead issue triage


• Identify gaps in data management standards and develop plans to close them


• Conduct concept testing and research to prototype toolsets and improve processes


• Mentor Data Engineers in continuous integration and continuous delivery


• Define key performance indicators and internal controls

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Mathematics, Statistics, or related field


• 7+ years of experience in data engineering, with demonstrated leadership in enterprise data platforms


• Advanced proficiency in SQL and Python


• Deep expertise in data integration, pipeline development, and large-scale data processing


• Strong experience implementing data quality frameworks and automated validation


• Advanced knowledge of data modeling, metadata, and lifecycle management


• Experience with data governance, lineage, and control frameworks


• Strong understanding of AI/ML data requirements and data readiness practices


• Proven ability to design solutions for scalable, high-performance analytics platforms


• Experience enabling AI-ready data ecosystems and advanced analytics platforms


• Demonstrated success implementing enterprise data quality programs and governance frameworks


• Strong knowledge of DataOps and MLOps practices


• Experience designing and supporting hybrid (cloud + on-prem) data architectures


• Background in regulated industries with audit, risk, and compliance requirements


• Proven track record of driving data strategy and platform modernization initiatives


• Ability to work 1st shift in the United States of America


• 40 hours per week

Core Competencies

Demonstrates expertise in data engineering, focusing on data integration, pipeline development, and governance frameworks. Proven ability to design scalable data architectures and implement data quality programs to support AI and advanced analytics initiatives.

Highest-signal resume keywords

• Data Engineering Leadership


• Advanced SQL Proficiency


• Python Programming
  
• Data Governance Frameworks


• DataOps and MLOps Practices

ATS Optimization Keywords

Hard Skills

• Data Integration


• Pipeline Development


• Data Quality Frameworks


• Data Modeling


• Metadata Management


• Large-Scale Data Processing


• AI/ML Data Requirements


• Hybrid Data Architectures


• Data Strategy Implementation


• Performance Analytics Design

Soft Skills

• Technical Thought Leadership


• Mentoring Data Engineers


• Collaboration with Subject Matter Experts

Industry Keywords

• Enterprise Data Platforms


• Regulated Industries


• Audit and Compliance


• Data Freshness Quality


• Operational Knowledge