Senior Data Engineer

About the Role

We are looking for a Senior Data Engineer to join our Data Science team. The Senior Data Engineer will lead the design and development of scalable, high-performance data architectures and models for both batch and streaming data processing. This person will define and execute a strategic Data Engineering Roadmap that maximizes the value of the organization's data assets and ensures alignment with long-term business goals.

This position is EST-based. Talkspace is headquartered in NYC.

What You'll Do

• Data Architecture and Modeling:

- Lead the design, development, and maintenance of scalable and high-performance data architectures and models supporting batch and streaming data processing.
- Define and drive the execution of a strategic Data Engineering Roadmap aligned with long-term business objectives.
- Own, enhance, and evolve critical datasets, streaming and batch pipelines, advanced data discovery, search experiences, and reporting/visualization tools.

• Database Processing and Management:

- Oversee complex ETL/ELT processes from diverse sources and manipulate large datasets.
- Spearhead the administration, tuning, and optimization of database systems for performance, reliability, and scalability.

• Continuous Improvement:

- Identify inefficiencies and optimization areas in data engineering workflows and technologies.
- Drive adoption of industry-leading best practices to enhance operational efficiency, reduce technical debt, and scale data engineering capabilities.

• MLOps Implementation:

- Develop and maintain MLOps pipelines automating deployment, monitoring, and management of machine learning models in production.
- Perform other related duties as assigned.

Qualifications

• BA/BS in Computer Science, Data Engineering, or a related field, or equivalent professional experience. Advanced degree preferred.
• 4-6 years of experience in data engineering or related roles manipulating and managing large datasets using Python, AWS, and SQL.
• Proven experience designing, building, and optimizing data warehouses (Redshift) with strong expertise in data warehouse design and dimensional modeling.
• Extensive experience with ETL/ELT processes and orchestration tools, particularly Airflow and DBT.
• Proficiency in AWS CDK for managing cloud infrastructure as code and automating deployments.
• Strong analytical and problem-solving skills with a focus on performance and efficiency.
• Demonstrated experience managing Google Looker.
• Familiarity with CircleCI / Airflow or similar tools.