Lead Analytics Engineer

Jobtailor; Deutschland; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

Jobtailor in Germany seeks a senior Analytics Engineer to own the architecture and roadmap for complex analytics initiatives, including semantic layers and AI-ready data foundations.

You will define KPI standards, lead semantic-layer design, mentor engineers, and collaborate across Data Science, Data Engineering, and Core Technology to deliver scalable data platforms.

Qualifikationen

• 6+ years in Analytics Engineering, Data Engineering or BI.
• 4+ years hands-on production experience with dbt including incremental patterns, macros, tests, and CI/CD design.
• 3+ years of deep experience with a cloud-based data warehouse (Snowflake preferred), incl. performance tuning and cost optimization.
• Expert-level SQL and dimensional data modeling with durable, well-tested models.
• Experience designing and operating a semantic or metrics layer as a single source of truth.
• Proven ability to mentor senior engineers and influence cross-functional directions.
• Excellent written and verbal communication to align engineers and non-technical stakeholders.

Aufgaben

• Own the technical architecture and roadmap for analytics initiatives, including semantic layer design and data foundation for AI/use cases.
• Architect the semantic and metrics standards so KPIs are defined, governed, and consumed consistently.
• Lead the design of an AI-ready data platform with trustworthy, production-ready modeling and governance.
• Drive dbt excellence: model architecture, materialization, performance tuning, macros, tests, and CI/CD scaling.
• Set high craftsmanship standards for SQL, modeling patterns, and data quality.
• Mentor Senior/Analytics Engineers through code reviews and design feedback.
• Partner with Analytics Engineering Manager on technical strategy, hiring, and roadmap planning.
• Lead partnerships with Data Science, Data Engineering, and Core Technology on critical-path work.
• Evaluate third-party data sources and tooling to elevate the platform.
• Champion data governance, lineage, observability, and compliance.

Kenntnisse

Analytics Engineering

SQL proficiency

Mentoring

Cross-functional collaboration

Architectural leadership

Communication skills

Tools

dbt

Snowflake

CI/CD

Observability tools

Jobbeschreibung

Responsibilities

• Own the technical architecture and roadmap for our most complex Analytics Engineering initiatives - including semantic layer design, source-of-truth consolidation, and the data foundation for AI and agent-based use cases
• Architect Forward's semantic layer and metrics standards so key business KPIs are defined once, governed clearly, and consumed consistently across dashboards, models, AI agents, and downstream products
• Lead the technical design of the AI-ready data platform - making the modeling, metadata, and governance decisions that make Snowflake Intelligence and other AI/agent capabilities trustworthy, performant, and production-ready
• Drive technical excellence across our dbt project: model architecture, materialization and incremental strategies, performance tuning, macros, testing patterns, and CI/CD practices that scale as data volume and team size grow
• Set and uphold a high bar for craftsmanship across the team - defining standards for SQL style, modeling patterns, documentation, and data quality, and modeling those standards in your own work
• Mentor Senior and Analytics Engineers through hands-on code review, pairing, and design feedback - accelerating their growth into stronger technical contributors
• Partner with the Manager of Analytics Engineering on technical strategy, hiring, and roadmap planning - acting as a deputy for technical decisions and unblocking the team on the hardest problems
• Lead deep technical partnerships with Data Science, Data Engineering, and Core Technology - owning schema migrations, feature deployments, and streaming pipeline contributions where Analytics Engineering is on the critical path
• Evaluate and operationalize high-value third-party data sources and emerging tooling (e.g., Snowflake Cortex, semantic layer frameworks, observability tools) and make recommendations that elevate the platform
• Champion data governance and quality at the platform level - including dbt tests, lineage, cataloging, observability, and compliance with security and regulatory standards - so both stakeholders and AI systems can trust the numbers

Requirements

• 6+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence
• 4+ years of hands-on production experience with dbt, including advanced patterns such as incremental strategies, macros, custom tests, and CI/CD design
• 3+ years of deep experience with a cloud-based data warehouse (Snowflake strongly preferred), including performance tuning and cost optimization
• Expert-level proficiency in SQL and dimensional data modeling, with a portfolio of durable, well-tested models that have served as foundational layers for an organization
• Demonstrated experience designing and operating a semantic layer or metrics layer that serves as an organizational source of truth
• Proven ability to mentor senior engineers, lead architectural decisions, and influence direction across cross-functional teams
• Excellent written and verbal communication skills - able to drive technical alignment with both engineers and non-technical stakeholders.