Data Engineer

Data Engineer

Position Purpose:

Senior Data Engineers are critical to designing, implementing, and optimizing scalable data infrastructure to support the data needs of THD. This role involves managing complex data pipelines, ensuring data quality and accessibility, and enabling data-driven insights that drive business decisions. With expertise in Google Cloud Platform (Google Cloud Platform), SQL, and data engineering best practices, this role will guide and mentor junior engineers, collaborate cross-functionally, and make large impacts to advancing the company's data architecture and strategy. The engineering process is highly dynamic, and engineers are expected to collaborate through user stories and support products as they evolve. Activities include using specific HD process techniques, integration, design, testing, and development. The role will interface with Business Stakeholders, Technology Infrastructure teams, and Development teams to ensure that business requirements are properly met within a data solution. The role may also be involved in performance tuning, testing, and product monitoring.

Engineers should be able to operate independently with minimum guidance from others, although will typically work as part of a team with varying skill levels to create, support, and deploy production applications. This role will review submitted code and provide feedback to improve, based on best practices.

Major Tasks and Responsibilities

60% Delivery and Execution Collaborates with other team members to develop, optimize, and maintain scalable ETL/ELT workflows and data pipelines. Works with team members to troubleshoot and resolve data issues. Implements best practices for data quality, security, and efficiency. Documents, reviews, and ensures that all quality and change control standards are met. Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable. Configures commercial off the shelf solutions to align with evolving business needs. Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively.

30% Support and Enablement - Mentor junior engineers, fostering skill development and adherence to best practices. Fields questions from other product teams or support teams. Monitors tools and participates in conversations to encourage collaboration across product teams. Provides application support for software running in production. Proactively monitors production Service Level Objectives for products. Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and quality.

10% Learning - Participates in learning activities around modern software design, data engineering, and development core practices (communities of practice). Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations.

Qualifications:

3-5 years of relevant work experience

Bachelor's degree in computer science, data engineering, or related field (or equivalent experience).

Strong proficiency in SQL, data processing, and a programming language (Python preferred).

Deep expertise in effective data warehouse engineering practices and platforms such as BigQuery, Snowflake, Synapse, etc.

Experience in version control systems (preferable Git)

Experience with Google Cloud Platform and data engineering components such as Cloud Composer, Cloud Functions, Dataproc, etc.

Experience with CI/CD (Jenkins)

Experience with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security

Strong problem-solving skills and attention to detail.

Knowledge, Skills, Abilities and Competencies:

Global Perspective

Manages Ambiguity

Nimble Learning

Self-Development

Collaborates

Cultivates Innovation

Situational Adaptability

Communicates Effectively