This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Analytics Engineer in Ireland.

This role offers the opportunity to build and scale the core analytics infrastructure powering decision-making across a fast-growing Web3 technology organization. You will design and own end-to-end data systems that transform raw operational, product, and business data into trusted insights used by teams across product, engineering, marketing, sales, and finance. Working in a highly technical, distributed environment, you will develop robust data pipelines, scalable datasets, and self-serve analytics products that enable data-driven decisions at every level. You will collaborate closely with leadership and cross-functional stakeholders to define key business metrics and ensure consistent, reliable reporting. This position blends data engineering, analytics engineering, and platform ownership in a high-impact, fast-paced environment. It is ideal for someone who thrives on building trusted data foundations that directly shape business strategy.

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Accountabilities:

Own and evolve end-to-end analytics data pipelines, including ingestion, transformation, orchestration, monitoring, and maintenance across warehouse and BI systems.
Design and build scalable, self-serve data products such as curated datasets, semantic layers, metric definitions, and dashboards for cross-functional use.
Implement strong data quality, observability, and reliability frameworks, including anomaly detection, lineage tracking, and pipeline health monitoring.
Develop and maintain key business analytics covering product performance, growth, retention, revenue, churn, and marketing funnel metrics.
Partner with stakeholders to define, structure, and standardize KPIs, ensuring alignment on metric definitions and business logic.
Translate product, engineering, and operational changes into robust analytics models, data pipelines, and reporting structures.
Document data systems, including architecture, definitions, ownership, and operational procedures to ensure transparency and maintainability.
Triage and resolve ad hoc analytics issues while converting recurring needs into scalable, long-term data solutions.

Requirements:

5+ years of experience in analytics engineering, data engineering, BI engineering, or similar data platform roles with production system ownership.
Advanced SQL expertise, including data modeling, transformation design, query optimization, and scalable dataset architecture.
Strong Python skills for data pipelines, automation, API integration, testing, and workflow development.
Hands-on experience with workflow orchestration tools such as Airflow, including DAG design, debugging, and operational maintenance.
Deep understanding of data quality, observability, lineage, and incident management for analytics systems.
Strong BI and dashboarding experience (preferably Metabase), with ability to design decision-driven, self-service analytics.
Solid understanding of SaaS and digital business metrics such as funnels, retention, cohorts, CAC, LTV, and revenue analytics.
Experience working with operational and engineering data such as system performance, logs, and reliability metrics.
AI-native working approach, leveraging modern tools for coding, automation, and documentation with strong validation discipline.
Excellent communication skills with the ability to align technical and non-technical stakeholders on data definitions and trade-offs.

Benefits:

Competitive USD-based salary aligned with experience and impact.
Stock options providing participation in company growth and success.
Fully remote, flexible work environment with global collaboration.
Flexible working hours focused on output and work-life balance.
Opportunity to work on cutting-edge Web3 and blockchain infrastructure.
Flat organizational structure enabling ownership, autonomy, and fast decision-making.
Collaboration with a diverse, international team across multiple time zones.
Access to modern tools and technologies in a rapidly evolving industry.

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How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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Senior Analytics Engineer

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Job Description