What will you do in this role?

The Principal Analytics Engineer designs, builds, and supports high-quality data products supported through data pipelines and data integrations, and/or data visualizations. It is critical to ensure reliability, performance, and cost efficiency while maintaining thorough documentation.

The Principal Analytics Engineer will use new and established automation and integration tools, Information Architecture strategy, frameworks, critical thinking, and problem-solving skills to build and support the ongoing development of data products.

The ideal candidate is outcome-focused and has a collaborative style that fosters teamwork. They will be required to work across multiple initiatives.

What will the employee do in this role?

• Lead the design, creation, and support of high-quality data products

• Build and manage data warehouses and data lakes

• Design and build data pipelines, data flows, and/or data visualizations to support data products

• Develop and maintain semantic models

• Focus on DevOps processes, reliability, performance, and cost optimization

• Implement data quality checks and validation processes to ensure data accuracy and reliability

• Collaborates with Data Services leadership to prioritize product roadmap

• Drive the adoption of new data technologies and tools to enhance data processing capabilities

• Lead cross-functional groups in large-scale data projects, ensuring alignment with business objectives

• Contribute to the process of making data architecture decisions

• Provide thought leadership in analytics engineering best practices and emerging technologies

• Coordinate with Data Governance to support the development and implementation of data governance frameworks and policies for data products

What Skills & Qualifications do you need?

Education

• BA\BS required; MBA or MS or equivalent a plus

• Certifications related to data and analytics engineering (e.g., Azure Data Factory, Microsoft Fabric, Power BI) preferred; Microsoft Fabric Analytics Engineer Associate will be required within 90 days if not already achieved

Required Qualifications

• 10+ years of data/analytics engineering experience

• Expert in SQL with knowledge of T-SQL and PL/SQL

• Expert in data engineering techniques, data pipeline development and/or data visualization development

• Applied experience transforming manual processes to industry standards

• Requires excellent analytical ability, attention to detail, and proven ability to work independently and in a team

• Ability to quickly adapt to changing priorities and generate innovative solutions

• Expert understanding of conceptual and logical data design

• Expert understanding of data mapping and lineage strategies

• Expert understanding of data modeling techniques such as 3rd normal form and star schema

Preferred Qualifications

• Financial services industry experience or other highly regulated industry experience

• Applied experience in Agile, SAFe, Scrum or Lean Six Sigma

• Familiarity data engineering development using Python and/or Scala

• Demonstrated understanding of data management practices and data governance process; familiarity with data governance tools such as Azure Purview

• Certifications related to Data Analytics and/or Data Engineering

• Proficient with building data pipeline / analytics solutions in a cloud data architecture, experience with Azure Data Solutions including Microsoft Fabric

• Familiarity with analytics process automation tools such as Alteryx

• Familiarity with object-oriented programming and the software development process

• Familiarity with source control tools such as git

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Required Skills

Required Experience

Critical Competencies

· Must be highly organized, self-motivated, and thoroughly attentive to detail in all actions.

· Must have excellent verbal, written, and interpersonal skills and be able to communicate across all levels and functions of the organization.

· Must be able to work effectively in a team environment.

· Must be able to function effectively and independently and meet deadlines with minimal supervision.