Director of Data Engineering

About The Position

We are looking for a visionary Director of Data Engineering to lead our data engineering, infrastructure, and analytics strategy.

In this role, you will oversee the foundation of our data-driven culture, ensuring that our infrastructure is scalable, secure, and high-performing. You will act as a strategic partner to the executive stakeholders, translating business goals into a robust technical roadmap to drive Rise to the next level of data-driven organization.

Responsibility

• Strategic Leadership: Direct the data engineering, data infrastructure, and MLOps functions. Define the long-term vision for our data ecosystem, moving toward a decentralized Data Mesh where R&D teams "own" their data product
• Stakeholder Management: Align data initiatives with global business objectives and provide transparency into the data roadmap
• Data & Cloud Infrastructure: Oversee the design and maintenance of our core data infrastructure. Drive FinOps initiatives to optimize cloud spend and compute efficiency for high-volume storag
• Architectural Excellence: Design real-time data architectures and implement Data Contracts to ensure reliability and quality across the entire engineering pipeline
• Team Development: Lead and mentor a multi-disciplinary team of engineers, fostering a "Product Engineering" mindset and a culture of technical excellence
• Collaboration: Bridge the gap between Software Engineering, Data Science, and Product. Ensure Data Science teams have the high-quality, model-ready data they need to drive innovation

Requirement

• Data Warehousing: Expert-level knowledge of modern Cloud Data Warehouses (e.g., BigQuery, Snowflake, or Redshift). Proven experience managing petabyte-scale datasets and optimizing for both performance and c
• Big Data Processing: Deep hands-on experience with Apache Spark (PySpark/Scala) for large-scale ETL and real-time data enrichm
• Workflow Orchestration: Proficiency in Apache Airflow or similar tools; ability to design complex, multi-tenant DAGs and manage production-grade orchestrat
• Streaming & Event-Driven Systems: Experience with high-throughput ingestion and messaging systems (e.g., Kafka, Pub/S
• Infrastructure & DevOps: Strong understanding of cloud infrastructure (GCP/AWS) and experience running production systems at sc
• AI/ML Foundations: Familiarity with MLOps and the infrastructure required to support AI applications (e.g., Vector Databases or model deployment pipelin

• 4+ years of experience in a leadership role within Data Engineering or high-scale infrastructure environmt
• 6+ years in Data Engineering, Big Data, or Infrastructure role
• Leadership: Proven experience in a management or lead role, with a track record of scaling teams and infrastructure in high-growth environmnt
• ents.Experience in high-scale, high-throughput environments (e.g., real-time bidding, adtech, or high-volume log processing) is a significant advan
• tage.Strong understanding of GCP/AWS cloud infrastructure and cloud cost manage
• ment.Passion for business results and product orientation with experience in building the technical requirements for internal prod
• Excellent problem-solving skills and the ability to make data-driven decis

Advantages

• Experience with data engineering of an adTech company or any other experience in the adTech industry
• Experience in creation of requirement document for Data Engineering teams
• Successful building and driving adoption of internal tools
• Experience with decision supporting systems, and automation of decisions.
• Experience with GenAI data technologies, data processing and optimization, e.g. optimizing vector DBs.