Data Engineer

Position Description

The Data Engineering function is growing across ingestion, integration, transformation, and consumption

capabilities to deliver data products that transform how the organization leverages data. The Data Engineering and

Platforms team is seeking an experienced Senior Data Engineer to provide technical leadership and expertise to

both internal and partner teams within the Enterprise Data environment. This role will be instrumental in shaping

technical roadmaps, defining best practices, and contributing significantly to architectural decisions to drive

innovation at scale.

This role demands deep technical expertise, strong problem-solving skills, and architectural understanding across

data engineering initiatives. It requires close collaboration with architects and stakeholders to contribute to

enterprise-wide data engineering strategies, ensuring scalable, resilient, and cost-optimized data solutions.

To be successful in this engineering role requires a highly motivated individual with an innovative mindset and

willingness to drive tangible outcomes. The individual must be able to articulate complex technical topics,

collaborate with internal and external partners, and ensure quality delivery of required data products.

Responsibilities

Lead the technical design and hands-on development of scalable, high-performance data platforms and

solutions provide technical guidance to the engineering team.

Drive data-driven decision-making to deliver measurable business impact across the organization.

Contribute to defining and implementing enterprise data architecture principles aligned with organizational data

strategy.

Modernize legacy data products to modern data architectures ensuring performance and scalability.

Establish standards, frameworks, and patterns aligned with security, compliance, and performance best

practices.

Provide hands-on technical guidance and mentor junior engineers.

Architect and oversee fault-tolerant, cost-optimized data pipelines across Azure, Databricks, and GCP.

Partner with security teams to ensure compliance with security and regulatory standards.

Collaborate with Product Owners, Data Architects, and Engineering Squads in agile delivery.

Evaluate new tools and trends contribute to AI-driven automation, DataOps, and DevSecOps adoption.

Lead technical discussions in sprints, backlog refinement, and iterative solution design.

Drive POCs, rapid prototyping, and pilot implementations for new approaches.

Provide advanced technical solutions for complex ingestion, processing, and storage challenges.

Ensure consistency in data engineering patterns across domains for a unified data ecosystem.

Qualifications

Bachelors Degree in Computer Science, Software Engineering, or equivalent professional experience.

47 years of experience delivering enterprise-scale data solutions in the cloud (Databricks, Azure, GCP

preferred).

Additional Skills / Preferences

Proven track record in leading and delivering complex data projects.

Expertise in data management, information integration, and analytics practices.

Experience with modern data architectures and methodologies (Domain-driven design, scalable pipelines,

DataOps CI/CD, API-centric design, SQL/NoSQL, FAIR principles).

Strong expertise in Azure Data Factory (ADF).

Proficiency with GitHub for version control and CI/CD workflows.

Experience in DevSecOps culture, CI/CD, and TDD practices.

Familiarity with ML workflows, data quality, and data governance.

Experience in complex, multi-stakeholder environments.

Experience mentoring junior engineers.

Strong interpersonal and communication skills.