Head of Data Engineer

Responsibilities:

• Translate business needs into clear and actionable technical requirements.
• Lead and manage the Data Engineering team to develop data Pipelines aligned with business needs.
• Ensure seamless ETL processes to support the company’s analytics requirements.
• Oversee the management and maintenance of data infrastructure.
• Collaborate with other departments to ensure data needs are met effectively.

Requirements:

Must Have

• Minimum D3/S1 degree in Information Technology (IT).
• At least 5–8 years of experience in building Scalable Data Architectures, managing data Pipelines and ETL processes, and leading teams to implement efficient, impactful data solutions.
• Data Architecture: Expertise in designing complex data architectures, including Data Lakes, data warehouses, and data marts.
• Data Pipeline Development (ETL/ELT): Proficiency with ETL/ELT tools like Apache Airflow, Talend, dbt, or Spark.
• Database Management and Query Optimization: Strong skills in managing and optimizing relational (SQL) and non-relational (NoSQL) databases, such as MySQL, PostgreSQL, MongoDB, and ClickHouse.
• Advanced proficiency in Python, Scala, or Java for managing data Pipelines.
• Streaming Data Technologies: Hands-on experience with tools like Kafka, Flink, and Debezium for real-time data processing.

Nice to Have

• Strong leadership skills to guide a technical team and provide strategic direction.
• Ability to convey technical information to non-technical stakeholders.
• Problem-solving capabilities to address data pipeline issues with effective solutions.
• Collaboration with business, infrastructure, and analytics teams.
• Strong time management to prioritize tasks and meet deadlines.
• Adaptability to learn new technologies and respond to evolving business needs.