Senior Data Engineer

About the role

Axial Search is a specialist executive search firm focused on leaders who help organizations navigate AI transformation. This data engineering role targets candidates with deep expertise in modern data stack tooling—cloud warehouses, orchestration frameworks, and streaming platforms—and a proven track record of scaling pipelines under real production constraints. The ideal engineer balances technical rigor with pragmatism, understands data quality deeply, knows when “good‑enough” is appropriate, and communicates trade‑offs clearly to cross‑functional stakeholders.

Responsibilities

• Design and build scalable data pipelines and architectures that ingest, transform, and serve data reliably at scale.
• Own end‑to‑end data pipeline development, from requirements gathering through deployment and monitoring in production environments.
• Partner with data scientists, analytics teams, and product engineering to understand data needs and translate them into robust technical solutions.
• Lead data quality initiatives, including validation frameworks, testing strategies, and monitoring to catch issues before they reach downstream consumers.
• Optimize data infrastructure for cost, latency, and reliability; drive architectural decisions that anticipate future scale.
• Document data lineage, transformation logic, and operational runbooks to enable team knowledge sharing and reduce onboarding friction.
• Mentor junior engineers on data engineering best practices and code review contributions to raise technical standards across the team.

Requirements

• 5+ years of professional data engineering experience, with demonstrated ownership of production data systems at scale.
• Strong hands‑on expertise with modern data stack tools—cloud data warehouses (Snowflake, BigQuery, Redshift), orchestration platforms (Airflow, dbt, Prefect), and distributed processing frameworks.
• Proven ability to design and implement data architectures that balance performance, cost, and maintainability in high‑throughput environments.
• Solid software engineering fundamentals: version control, testing, code review discipline, and ability to write production‑grade code in Python, Scala, SQL, or similar languages.
• Experience collaborating with stakeholders across data science, analytics, and engineering to scope requirements and communicate technical constraints.
• Track record of shipping production systems and maintaining them through operational incidents and scaling challenges.

Pay

Compensation for this cohort typically lands between $150K and $290K annually.