Director, Data Engineering

Accountabilities

In this role, you will define and lead the engineering vision for a scalable, high-quality data platform while actively contributing to its technical evolution:

• Lead, mentor, and grow a team of data engineers, fostering a culture of ownership, collaboration, and technical excellence.

• Contribute hands-on to the design and development of data pipelines, integrations, and core platform components.

• Own and evolve a Databricks-based lakehouse architecture, ensuring scalability, performance, and maintainability.

• Define and enforce engineering standards across ingestion, transformation (dbt), testing, CI/CD, documentation, and observability.

• Design robust ingestion frameworks for complex, multi-source environments, including M&A-driven integrations.

• Ensure reliable data pipelines with strong monitoring, lineage, and full historical traceability.

• Partner with analytics and governance teams to ensure data models and contracts support downstream business use cases.

• Drive operational excellence, including incident response, reliability improvements, and SLA adherence.

• Support hiring, team scaling, and long-term engineering capacity planning.

Requirements

The ideal candidate combines strong technical depth in data engineering with proven leadership experience in complex, fast-moving environments:

• 3+ years in data engineering with at least 2+ years in a senior or leadership role.

• Strong hands-on expertise with Databricks (Delta Lake, Unity Catalog, Spark) and modern data lakehouse architectures.

• Proficiency in Python and SQL for building scalable data pipelines.

• Experience with dbt or similar transformation frameworks.

• Strong background in building and operating data pipelines using tools such as Fivetran, Airflow, or equivalents.

• Deep understanding of data modelling, data warehousing, and distributed data systems.

• Proven ability to define and enforce engineering best practices (testing, CI/CD, observability, documentation).

• Experience working with cloud platforms, ideally AWS.

• Strong communication skills with the ability to translate technical decisions into business impact.

• Ability to balance hands-on engineering with leadership and cross-functional collaboration.

• Experience in complex environments such as M&A, multi-system integrations, or platform migrations is highly valuable.

• Familiarity with data quality, governance, BI tools, and modern analytics ecosystems is a plus.

Benefits

• Competitive salary with performance-related bonus opportunities.

• Flexible working arrangements and remote-first environment.

• Comprehensive health, wellness, and employee support programs.

• Flexible time off policies to support work-life balance.

• Career development programs and long-term growth opportunities.

• Collaborative and innovative engineering culture.

• Opportunity to shape a modern enterprise data platform from the ground up.

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.

#LI-CL1