Senior PySpark Engineer
3 months ago
Job Overview
Wise Analytics is seeking a highly skilled and experienced Senior Data Engineer to lead the design and architecture of data engineering solutions for our global clients in the retail and finance domains. The ideal candidate will be an independent contributor capable of managing a technical team, handling stakeholders, and ensuring timely delivery of complex projects. Expertise in technologies such as GCP, Airflow, Databricks, Kafka, and experience with creating data lakes, data warehouses, or lakehouses is essential.
Key Responsibilities
Design and Architecture
- Lead the design and architecture of scalable and efficient data engineering solutions on GCP, leveraging technologies such as PySpark, Databricks and Kafka.
- Develop data models and ETL/ELT pipelines to support data lakes, data warehouses, and lakehouses for advanced analytics and reporting.
Team Leadership
- Manage and mentor a team of data engineers, providing technical guidance and ensuring best practices are followed.
- Foster a collaborative and innovative team environment, encouraging continuous learning and improvement.
Project Management
- Oversee project timelines, budgets, and resources, ensuring successful delivery of complex data engineering projects.
- Collaborate with cross-functional teams to align project goals with business objectives and stakeholder requirements.
Stakeholder Management
- Engage with senior stakeholders to understand business needs and translate them into technical requirements.
- Present project updates, technical solutions, and data insights to stakeholders in a clear and concise manner.
Technical Expertise
- Implement and optimize data processing workflows using Airflow, ensuring reliability and efficiency.
- Develop and maintain real-time data streaming solutions with Kafka to support high-velocity data ingestion and processing.
- Ensure data quality, security, and governance across all data engineering processes and solutions.
Qualifications
Education
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Experience
- 15+ years of experience in data engineering, with a strong background in designing and implementing data solutions.
- Proven experience in a leadership role, managing technical teams and handling complex projects.
Technical Skills
- Expertise in cloud platforms, particularly GCP.
- Proficiency with PySpark and Databricks for data processing and analytics.
- Strong experience with Apache Airflow for orchestrating data workflows.
- Extensive knowledge of Apache Kafka for real-time data streaming.
- Familiarity with data modeling, ETL/ELT processes, and building data lakes/warehouses/lakehouses.
Soft Skills
- Excellent communication and presentation skills, with the ability to articulate technical concepts to non-technical stakeholders.
- Strong problem-solving skills and a proactive approach to identifying and addressing challenges.
- Ability to manage multiple priorities and deliver high-quality results under tight deadlines.
Preferred Qualifications
- Experience in the retail and finance domains.
- Certification in GCP or related technologies.
- Knowledge of additional data engineering tools and frameworks.
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