Director – Data Engineering
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Job Description
Director leading and scaling data engineering function for a Weekday's client. Building efficient data platforms powering analytics and business intelligence across the organization.
Responsibilities:
- 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.
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