Director – Data Engineering

Role Overview

• This role is for one of the Weekday's clients
• We are seeking an experienced and visionary Director – Data Engineering to lead and scale our data engineering function.
• You will play a critical role in building robust, scalable, and efficient data platforms that power analytics, machine learning, and business intelligence across the organization.

Requirements

• Min Experience: 12 years
• Lead the design, development, and optimization of scalable data pipelines, data lakes, and data warehouses.
• Define and implement the overall data engineering strategy aligned with business goals and future growth.
• Architect modern data platforms leveraging cloud technologies such as AWS, Azure, or GCP.
• Drive best practices in data modeling, ETL/ELT processes, data governance, and data quality management.
• Collaborate closely with data scientists, analysts, and business stakeholders to enable data-driven decision-making.
• Build and mentor a high-performing team of data engineers, fostering a culture of innovation, ownership, and continuous improvement.
• Oversee large-scale data integration efforts involving structured and unstructured data sources.
• Ensure data security, compliance, and privacy standards are adhered to across all systems.
• Evaluate and implement new tools, frameworks, and technologies to enhance data capabilities.
• Establish performance benchmarks and continuously improve system reliability, scalability, and efficiency.
• Strong expertise in Data Engineering fundamentals including distributed data processing, data architecture, and pipeline optimization.
• Hands-on experience with big data technologies such as Spark, Hadoop, Kafka, and Airflow.
• Proficiency in SQL, Python, Scala, or Java for building and managing data workflows.
• Deep understanding of cloud-based data platforms and services (e.g., AWS Redshift, BigQuery, Azure Data Factory).
• Experience with real-time and batch data processing systems.
• Strong knowledge of data warehousing concepts, dimensional modeling, and data lake architectures.
• Familiarity with DevOps practices, CI/CD pipelines, and infrastructure as code.
• Proven ability to design systems that handle high data volume, velocity, and variety.
• Demonstrated experience in leading and scaling data engineering teams in fast-paced environments.
• Strong stakeholder management and communication skills, with the ability to translate technical concepts into business value.
• Strategic thinker with a problem-solving mindset and attention to detail.
• Ability to drive cross-functional collaboration and influence decision-making at senior levels.
• Passion for innovation and staying updated with emerging trends in data and analytics.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience in building data platforms supporting AI/ML initiatives is a plus.
• Prior experience in a leadership role within high-growth or enterprise environments.

Tech Stack

• Airflow
• Amazon Redshift
• AWS
• Azure
• BigQuery
• Cloud
• ETL
• Google Cloud Platform
• Hadoop
• Java
• Kafka
• Python
• Scala
• Spark
• SQL