Programmer/Analyst: III (Senior)

Data Engineer Lead

Role Summary

The Data Engineer Lead plays a critical role in building, optimizing, and operationalizing enterprise data pipelines that support Company's data and analytics initiatives. This role combines deep hands-on technical leadership with team development and cross-functional collaboration.

The position leads the design, development, and production deployment of scalable data pipelines that deliver curated, high-quality data to key consumers such as business analysts, data scientists, and other enterprise stakeholders. The role also ensures strong data quality standards so data is accurate, complete, consistent, and aligned with defined business rules.

Key Responsibilities

Architect, build, maintain, and optimize enterprise-scale data pipelines.

Lead efforts to modernize and automate data integration and data management infrastructure.

Partner closely with business analysts and data science teams to refine data requirements and ensure data is consumable for analytics and reporting use cases.

Move data pipelines efficiently and reliably into production environments.

Implement and validate data quality checks to ensure data integrity and compliance with business rules.

Collaborate with data governance teams to vet, promote, and publish curated datasets to enterprise data catalogs for governed reuse.

Train and mentor team members and cross-functional partners on data pipelining, preparation techniques, and best practices.

Serve as a technical leader and escalation point for complex data engineering challenges.

Communicate complex technical concepts and outcomes to both technical and non-technical audiences.

Provide leadership, coaching, and mentorship to develop team capabilities.

Work with stakeholders to clearly understand business needs and ensure data solutions meet those needs.

Anticipate technology trends and assess the impact of emerging technologies on Company's data strategy.

Lead through change and model best practices in delivery, collaboration, and professionalism.

Perform other duties as assigned. Basic Qualifications

Bachelor's degree in Computer Science, Statistics, or a related field.

7+ years of experience in data management disciplines, including data integration, modeling, optimization, and data quality.

7+ years of experience with database programming languages and advanced analytics. Preferred Qualifications

Master's degree in Computer Science, Statistics, or a related field.

Hands-on experience with data testing and validation frameworks.

Demonstrated success using data preparation and data engineering tools.

Extensive experience with data engineering platforms and tooling (e.g., AWS Glue, Lambda, Athena, or similar technologies).

Strong expertise with BI and analytics tools.

Experience with open-source and commercial data science platforms.

Familiarity with Agile or Lean development methodologies.

Strong understanding of modern data management architectures and processes.

Proven ability to design and manage scalable data pipelines and pipeline architectures.

Experience working with large, heterogeneous datasets to extract business value.

Strong DevOps experience, including version control, automated builds, testing, and release management.

Proven ability to lead and collaborate across cross-functional teams.

Ability to train and mentor junior team members.

Willingness and ability to learn new technologies quickly.

Prior experience in Financial Services is a plus.

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