Senior Data Commercial Engineer

Jobtailor; Deutschland; Remote; EUR 90.000 - 140.000; Vollzeit

Zusammenfassung

Jobtailor in Germany seeks a senior Data Platform Engineer to lead cross-functional data engineering, shaping enterprise-grade data models and governance. You will optimize Databricks pipelines, enforce Unity Catalog, monitor data reliability, and mentor teams on trusted datasets and best practices. This role requires hands-on coding in Python/PySpark/SQL and experience with Terraform and Airflow.

Local candidates preferred; on-site collaboration with German teams and stakeholders is expected.

Qualifikationen

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• 5+ years of experience in data engineering, analytics engineering, or data platform roles.
• 3+ years building production workloads in Databricks or similar Spark environments.
• Strong expertise in Databricks, Delta Lake, Lakehouse architecture, and Unity Catalog, including governance, permissions, and data certification standards.
• Advanced programming skills in Python, PySpark, and SQL.
• Experience in analytical SQL, distributed data processing, production-grade pipelines, and automation.
• Proven experience with data quality, observability, monitoring, anomaly detection, SLAs, validation, lineage, and self-healing pipeline frameworks.
• Strong knowledge of data modeling, partitioning, file compaction, query/performance tuning, compute optimization, and workload isolation for large-scale production environments.
• Ability to translate technical requirements into business-aligned data solutions, standardise best practices, mentor teams.
• Preferably work with Terraform and orchestration tools such as Airflow or Databricks Workflows.
• Domain experience in gaming/hospitality, loyalty/customer engagement, or marketing/commercial analytics is preferred.

Kenntnisse

Python Programming

PySpark

SQL

Data Quality

Observability

SLA & Validation

Mentoring

Problem Solving

Collaboration

Ausbildung

Bachelor's degree in Computer Science, IT, or related field

Tools

Databricks

Delta Lake

Unity Catalog

Terraform

Airflow

Databricks Workflows

Jobbeschreibung

• Lead cross-functional efforts to define and maintain certified business definitions, KPIs, metrics, and logic across assigned data domains
• Design, document, and maintain enterprise-ready curated tables and high-performance data models in Databricks aligned to business and analytical needs
• Optimize data pipelines, partitioning, file compaction, compute utilization, and query costs to improve performance, scalability, and production stability
• Enforce Unity Catalog governance standards, including data ownership, permissions, certification, and access management workflows
• Establish and monitor data reliability standards, including freshness SLAs, completeness thresholds, schema drift detection, and automated anomaly monitoring
• Own incident response, pipeline triage, and root-cause analysis for data failures, performance issues, and metric discrepancies
• Serve as the primary data reliability owner, driving continuous improvement while training teams on certified datasets, governance practices, and trusted data usage

Requirements

• Bachelor’s degree in Computer Science, Information Technology, or a related field required
• 5+ years of experience in data engineering, analytics engineering, or data platform roles
• 3+ years building production workloads in Databricks or similar Spark environments
• Strong expertise in Databricks, Delta Lake, Lakehouse architecture, and Unity Catalog, including governance, permissions, and data certification standards
• Advanced programming skills in Python, PySpark, and SQL
• Experience in analytical SQL, distributed data processing, production-grade pipelines, and automation
• Proven experience with data quality, observability, monitoring, anomaly detection, SLAs, validation, lineage, and self-healing pipeline frameworks
• Strong knowledge of data modeling, partitioning, file compaction, query/performance tuning, compute optimization, and workload isolation for large-scale production environments
• Ability to translate technical requirements into business‑aligned data solutions, standardise best practices, mentor teams
• Preferably work with Terraform and orchestration tools such as Airflow or Databricks Workflows
• Domain experience in gaming/hospitality, loyalty/customer engagement, or marketing/commercial analytics is preferred

Core Competencies

Demonstrates expertise in data engineering and analytics, with a strong focus on Databricks, Delta Lake, and data governance. Capable of optimizing data pipelines and ensuring data reliability while mentoring teams on best practices.

Highest-signal resume keywords

• Databricks Expertise
• Data Governance Standards
• Python Programming
• Data Quality Monitoring
• Data Modeling

Hard Skills

• Data Engineering
• Analytics Engineering
• Production Workloads
• Analytical SQL
• Distributed Data Processing
• Data Quality
• Data Modeling
• Performance Tuning
• Automation
• Root-Cause Analysis

Soft Skills

• Mentoring
• Collaboration
• Problem‑Solving

Industry Keywords

• Gaming
• Hospitality
• Loyalty
• Customer Engagement
• Marketing Analytics

Tools & Technologies

• Databricks
• Delta Lake
• Unity Catalog
• Terraform
• Airflow