Responsibilities

Position Summary

A Cloud Data Engineer Lead is a high-level professional responsible for designing, developing, and maintaining the data architecture in our organization. This role is responsible for overseeing the technical aspects of data management, including data integration, processing, storage, and retrieval.

The Cloud Data Engineer Lead provides technical leadership to a team of Data Engineers in the enablement and support of our cloud data platform, creation and maintenance of data pipelines, data product development, and data governance patterns to ensure the timeliness and quality of data. The role is responsible for ensuring that data is accurate, reliable, and available to Analysts, Data Scientists, and other stakeholders within our organization.

Our Data Engineering teams work in a highly collaborative environments, engage in daily standups, operate within Agile development practices, and participate in a GitOps development model in that everything is code.

Salary Range

The salary range for this position is $98,400. - $199,000/Yr.. Final compensation will be determined by location, skills, experience, qualifications and the career level at which the position is filled.

Key Accountabilities

Key Accountability 1: Data Engineering and Architecture Strategic Leadership

• Provide direction for the organization’s data engineering and architecture strategy.
• Make final decisions on data infrastructure design and tool selection, balancing business needs with technical feasibility.
• Collaborate on requirements gathering while owning the architectural vision and execution.
• Champion data management best practices across the organization.

Key Accountability 2: Engineering Execution and Technical Implementation

• Write production-quality code and implement scalable ETL pipelines using tools like AWS, S3, Glue, Lambda, and Databricks.
• Apply business intelligence best practices such as dimensional modeling and distributed data processing.
• Design, build, and maintain modern cloud-based data platforms to support enterprise data needs including integrations, analytics, and AI.

Key Accountability 3: Team Development and Cross-Functional Collaboration

• Bootstrap and grow the data engineering team, setting standards and mentoring new members.
• Translate business requirements into technical solutions, ensuring alignment with broader organizational goals.
• Enable data-driven decision-making by delivering reliable analytics pipelines and insights.

Key Competencies for Position

• Promotes Change - Actively seeks information to understand the rationale, implications, and impact for changes. Remains agile by quickly modifying daily behavior, leveraging resources, and trying new approaches to effectively embrace change. Willing to act quickly, learn and adjust as needed. Identifies and recommends changes to leadership to improve performance. Aligns activities to meet individual, team and organizational goals
• Strategy in Action - Breaks down larger goals into smaller achievable goals and communicates how they are contributing to the broader goal. Actively seeks to understand factors and trends that may influence role. Anticipates risks and develops contingency plans to manage risks. Identifies opportunities for improvement and seeks insights from other sources to generate potential solutions. Aligns activities to meet individual, team and organizational goals.
• Compelling Communication - Effectively and transparently shares information and ideas with others. Tailors the delivery of communication in a way that engages the audience and that is easy to understand and retain. Unites others towards common goal. Asks for others' opinions and ideas and listens actively to gain their support when clarifying expectations, agreeing on a solution and checking for satisfaction.
• Makes Decisions & Solves Problems - Takes ownership of the problem while collaborating with others on a resolution with an appropriate level of urgency. Collaborates and seeks to understand the root causes of problems. Evaluates the implications of new information or events and recommends solutions using decisions that are sound based on what is known at the time. Takes action that is consistent with available facts, constraints and probable consequences.

Qualifications and Education Requirements

• S. degree in a related field and 7 to 9 years professional experience OR a total of 7 plus years' experience as Senior Data Engineer, Senior Software Engineer, or equivalent.
• 5 plus years working in AWS Cloud (AWS Solution Architect Certification is a plus) and hybrid cloud environments.
• 7 plus years working with data warehouse platforms.
• Coding experience in SQL and scripting languages such as Python and Bash and expert working knowledge of the Spark platform, preferably in a cloud data platform environment such as Databricks.
• Experience working with large and complex data sets with multi-terabyte scale is a plus.
• Knowledge of Agile and GitOps methodologies
• Banking experience / knowledge is a plus
• Ability to communicate effectively, both orally and in writing, with clients and groups of employees to build and maintain positive relationships
• Strong leadership and communication skills. You must be able to collaborate with other teams, effectively manage projects, and communicate technical information to non-technical stakeholders.