Senior Analytics Engineer - Monetization & Data Pipelines

Innodata Inc.; Canada; Remote; CAD 130,000 - 150,000; Full time

Job summary

Innodata invites an accomplished Staff/Lead-level Data Analyst to join the Monetization Data Science & Analytics team as a senior IC and technical leader. You will own advertiser revenue analytics, monetization metrics, and growth dashboards, collaborating with Data Scientists, PMs, and engineers to deliver end-to-end insights.

You will lead data modeling, production SQL pipelines, and dashboards (Tableau/Superset), establish data quality standards, and mentor peers while driving cost-efficient,

Qualifications

• 9+ years of combined experience in Data Analytics, BI, or Analytics Engineering.
• 3+ years at Senior level or above in a high-scale tech, ads-tech, marketplace, or fintech company.
• Experience as the most senior analytics IC on an embedded team or readiness for that role.

Responsibilities

• Partner with Data Scientists and Product on the hardest analytics problems; drive metric definitions and governance.
• Architect and own production SQL pipelines, data models, and data cubes; oversee data quality and reconciliation.
• Own executive dashboards in Tableau / Superset and enable self-serve analytics across Monetization.
• Lead end-to-end analytics initiatives from data modeling to dashboard rollout with minimal supervision.
• Review and coach peers to raise the team’s analytics bar.

Skills

SQL proficiency

Data modeling

Airflow

Python (pandas/PySpark)

Dashboard design

dbt or equivalent

Tableau/Superset

Cross-functional collaboration

Leadership/mentoring

Tools

Presto/Trino/Hive

Spark SQL

Airflow DAGs

Tableau

Job description

Innodata invites an accomplished Staff/Lead-level Data Analyst to join the Monetization Data Science & Analytics team as a senior IC and technical leader. You will own advertiser revenue analytics, monetization metrics, and growth dashboards, collaborating with Data Scientists, PMs, and engineers to deliver end-to-end insights.

You will lead data modeling, production SQL pipelines, and dashboards (Tableau/Superset), establish data quality standards, and mentor peers while driving cost-efficient,