Data Platform Tech Lead

Clasp • Boston, MA

3d • $170,000 - $185,000 • Hybrid

About The Position

At Clasp, our full-stack Data team is responsible for building and operating the data backbone that connects our go-to-market systems, internal application systems, and our data warehouse. As we scale, we’re evolving the team’s structure: the core will focus on data orchestration, reliability, and interoperability, with some additional downstream reporting & analytics ownership as we scale the business. We’re seeking a strong leader to own the roadmap and execution of this transformation.
You will own the design, build-out, and operation of the data infrastructure that moves data reliably and consistently between systems, into our data warehouse, and out to analytics and consumer layers. You’ll lead a small team, define SLAs, build observability, and drive standards. We will empower you to act as a product owner for the “data as infrastructure” layer. You will partner closely with reporting, BI, and analytics stakeholders to ensure data flows and semantic models are fit for purpose.

Requirements

• 5+ years of experience in data engineering / data infrastructure roles, of which 2+ years managing/leading other engineers or architects.
• Expert experience with orchestration tooling (e.g., Airflow, Dagster), ingestion frameworks, cloud platforms (AWS/GCP/Azure), and data-warehouse technologies (Snowflake, BigQuery, Redshift, etc).
• Expert experience with data modeling, semantic layers (dbt or equivalent), metadata/lineage tooling, data quality frameworks.
• Proven track record designing and implementing data pipelines/infrastructure across multiple source systems into a data warehouse/lakehouse environment.
• Prior experience partnering with analytics/business teams (even if not owning dashboards) — able to translate needs into infrastructure requirements and deliver.
• Excellent verbal and written communication skills; ability to present to senior leadership and cross-functional audiences.
• Experience building or improving observability, monitoring, alerting for data pipelines.
• Bachelor’s degree in computer science, engineering, mathematics or equivalent (or equivalent real-world experience).

Nice To Haves

• Strong knowledge of API design, data contracts, system interoperability, micro-services or event-driven data architectures is a plus.
• Master’s or additional certifications are a plus.

Responsibilities

• Own the architecture and operational health of the data-orchestration layer (ingestion, transformation, movement, observability) across internal systems, go-to-market systems (CRM, CS, etc.), and the data warehouse.
• Lead a team of data engineers/ETL analysts on day-to-day project work
• Define with leadership and enforce data pipelines' SLAs, error-recovery strategies, schema change management, metadata/lineage documentation.
• Lead cross-system interoperability work: identify how data flows between source systems, warehouse, downstream consumers; design abstractions; reduce redundancy and latency.
• Partner with reporting/analytics teams to ensure data models (via e.g., dbt) align with consumption needs, but shift ownership of reporting to those teams.
• Own and evolve tooling around data quality, observability, lineage, and cataloging; propose infrastructure improvements.
• Evangelize “data as product/infrastructure” mindset across the organization: define APIs, data contracts, service level commitments to downstream analytics users.

Benefits

• Compensation: The salary range for this position is competitive and will be commensurate with the candidate's experience, qualifications, and industry knowledge, ranging between $170,000 to $185,000 annually.
• In addition to the base salary, we offer an attractive equity component as part of our compensation package, providing an opportunity for eligible employees to share in the success and growth of our company.
• We are committed to offering competitive compensation and benefits packages to attract and retain top talent.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level