Data Engineering Lead

Responsibilities & Key Deliverables

Engineering Lead / BI Architect provide vision and direction for the data engineering and BI analytics teams, aligning their efforts with the organization's overall business goals and strategies. Oversee the design, implementation, and maintenance of robust data pipelines and architectures that ensure the efficient collection, storage, and retrieval of data. Lead the development of advanced analytics and reporting frameworks that transform raw data into actionable insights, enabling informed decision-making across the organization. Establish and enforce data governance policies to ensure data accuracy, consistency, and security, thereby maintaining high data quality standards across all organizational data assets. Work closely with other departments, such as IT, marketing, finance, and operations, to understand their data needs and deliver tailored BI solutions that drive business performance. Mentor and develop a high-performing team of data engineers, analysts, and BI professionals, ensuring they have the skills and resources needed to succeed and contribute to the organization’s data-driven objectives.

Experience

1. Data Architecture Design:
   • Develop and implement data architectures that align with the organization’s business goals.
   • Design data models, establish data standards, and oversee data integration, migration, and management processes.
   • Architect and optimize data storage and retrieval systems to handle large-scale data processing effectively.
2. Leadership and Mentorship:
   • Lead and mentor a team of data engineers in designing and developing data pipelines, ETL/ELT processes, and data integration solutions.
   • Manage project priorities, allocate resources, and track progress to ensure timely delivery of projects.
3. Data Governance and Security:
   • Create and maintain data dictionaries, providing context and clarity for organizational data assets.
   • Implement and enforce data governance policies and security protocols to protect sensitive data.
4. Collaboration and Stakeholder Communication:
   • Partner with database administrators, developers, data analysts, and other IT professionals to align data architecture with organizational systems.
   • Engage with stakeholders to understand business requirements and ensure alignment of data solutions with strategic objectives.

Qualifications

1. Education and Certification:
   • Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
   • Certifications in Database Management or Cloud Data Architecture (e.g., GCP, AWS, Azure) are preferred.
2. Technical Expertise:
   • Proven expertise in data modelling and design, including conceptual, logical, and physical data models.
   • Advanced knowledge of ETL/ELT processes and data integration workflows.
   • Proficiency with a variety of data technologies, including relational databases, NoSQL databases, data warehouses, and data lakes.
   • Strong hands-on experience with tools such as Apache Kafka, Apache Spark, Hadoop, and PySpark.

General Requirements

Programming expertise in languages like Python,Scala and Java