Senior Data Platform Lead

Jobtailor; Deutschland; Hybrid; EUR 120.000 - 160.000; Vollzeit

Zusammenfassung

Jobtailor is seeking a senior data platform leader to own the Databricks-driven strategy, architecture, and roadmap in a complex enterprise. You will define federated platform options, drive reliability and cost optimization, and set engineering standards for CI/CD and IaC.

You will oversee a team of 4–7 engineers and collaborate with governance leads to deliver scalable data products. The role requires deep Databricks expertise, strong cloud infra knowledge, and fluency in English.

Qualifikationen

• Around 10+ years of experience leading data platform teams in complex enterprises.
• Deep hands-on Databricks expertise (Spark, Delta Lake, Unity Catalog, Workflows).
• Strong lakehouse architecture and cloud-native infra (Azure preferred / AWS / GCP).
• Experience owning an end-to-end technical platform (reliability, security, cost, roadmap).
• Ability to manage demand with business and technology stakeholders and deliver outcomes.
• Previous team leadership and cross-functional collaboration experience.
• Familiarity with data governance, cataloguing, and metadata management.
• Fluency in English.
• Background in data integration, pipelines, event streaming, or ETL/ELT tooling is highly desirable.
• Experience with large-scale strategic data programs; exposure to data mesh or data ownership models is desirable.
• Familiarity with MLflow, feature store, or Databricks Model Serving is desirable.

Aufgaben

• Own the technical strategy, architecture, and roadmap for the data platform centered on Databricks.
• Define platform options and roles in the federated environment and ensure governance.
• Lead platform reliability, performance, SLA compliance, and risk reduction.
• Establish engineering standards including CI/CD, IaC, and testing practices.
• Oversee Databricks clusters, cost management, and resource optimization.
• Drive best practices across Delta Lake, Unity Catalog, MLflow, and related components.
• Create data products that serve business and consumer needs.
• Collaborate with data architects, product owners, and governance leads.
• Translate requirements into platform solutions, balancing speed and integrity.
• Directly manage and develop 4-7 data/platform engineers/consultants.
• Foster engineering excellence, continuous improvement, and collaboration.
• Manage third-party vendor relationships and strategic partnerships.
• Support financial planning up to a three-year horizon.
• Work in a hybrid model with office attendance per local regulations and travel.

Kenntnisse

Databricks Expertise

Lakehouse Architecture

Data Governance

Data Integration

Team Leadership

Executive Presence

Influencing Without Authority

Growth Mindset

Collaborative Problem-Solving

Commitment to Team Development

Tools

ADF

Dbt

Fivetran

Kafka

MLflow

Databricks

Jobbeschreibung

• Own the technical strategy, architecture, and roadmap for the organization's data platform, with Databricks as the primary compute and analytics engine


• Define platform options and roles and responsibilities in the federated environment


• Lead platform reliability, performance, scalability, SLA compliance, and operational risk reduction


• Establish and enforce engineering standards, including CI/CD, infrastructure-as-code, and testing practices


• Oversee Databricks cluster configuration, cost management, and resource optimization


• Drive adoption of best practices across Delta Lake, Unity Catalog, MLflow, and related components


• Create a business- and consumer-oriented data products shopping experience


• Technically realize data governance and data quality frameworks with the Enterprise Data Governance team


• Triage and prioritize platform demand from business units, analytics teams, and product owners


• Translate stakeholder requirements into platform solutions while balancing delivery speed, architectural integrity, and roadmap priorities


• Serve as senior technical contributor and platform authority on enterprise data transformation programs


• Collaborate with data architects, data product owners, and data governance leads


• Provide technical due diligence and risk assessment for tools, vendors, and integration patterns


• Contribute to data strategy documentation, business cases, and executive presentations


• Lead or oversee batch ingestion, event streaming, and API-based data movement patterns


• Ensure connectivity between Databricks and upstream/downstream systems


• Evaluate and manage integration tooling such as ADF, dbt, Fivetran, and Kafka


• Define standards for data contracts, schema management, and pipeline observability


• Directly manage and develop 4-7 consultants who are data and platform engineers


• Foster engineering excellence, continuous improvement, and collaborative problem-solving


• Manage third‑party vendor relationships


• Support financial planning up to a three-year horizon


• Work in a hybrid model with office attendance aligned with local regulations and regular travel

Requirements

• Around 10+ years of experience leading data platform and/or data engineering teams in a complex enterprise environment


• Deep hands-on expertise with Databricks, including Spark, Delta Lake, Databricks SQL, Workflows, and Unity Catalog


• Strong understanding of lakehouse architecture and cloud-native data infrastructure (Azure preferred / AWS / GCP)


• Experience owning a technical platform end-to-end, including reliability, security, cost, and roadmap


• Track record of working across business and technology stakeholders to manage demand and deliver outcomes


• Previous experience leading a team


• Familiarity with data governance, data cataloguing, and metadata management practices


• Fluency in English


• Background in data integration, including pipeline design, event streaming, or ETL/ELT tooling (highly desirable)


• Experience contributing to large-scale strategic data programs (highly desirable)


• Exposure to data mesh, data product thinking, or domain-oriented data ownership models (highly desirable)


• Familiarity with MLflow, Feature Store, or Databricks Model Serving (highly desirable)


• Executive presence and ability to influence without authority


• Growth mindset and commitment to personal and team development


• Reference to the Leadership Framework is checked during the recruitment process

Core Competencies

Demonstrates expertise in leading data platform strategies and architectures, particularly with Databricks and cloud-native data infrastructures. Proven ability to manage cross-functional teams, drive data governance, and deliver high-quality data products while ensuring operational excellence.

Highest-signal resume keywords

• Databricks Expertise


• Lakehouse Architecture


• Data Governance


• Data Integration


• Team Leadership

ATS Optimization Keywords

Hard Skills

• Databricks


• Spark


• Delta Lake


• Databricks SQL


• Workflows


• Cloud‑Native Data Infrastructure


• Pipeline Design


• ETL/ELT Tooling


• Data Cataloguing


• Metadata Management

Soft Skills

• Executive Presence


• Influencing Without Authority


• Growth Mindset


• Collaborative Problem-Solving


• Commitment to Team Development

Industry Keywords

• Data Platform


• Data Engineering


• Data Governance Frameworks


• Data Mesh


• Domain-Oriented Data Ownership

Tools & Technologies

• ADF


• Dbt


• Fivetran


• Kafka


• MLflow