Senior Data Engineer Assistant Vice President

What you'll do

• Design, develop, and maintain scalable data pipelines using Big Data technologies like Hadoop, Spark, Kafka, and Hive.
• Implement and optimize ETL/ELT processes for data ingestion, cleansing, and transformation into data warehouses and lakes.
• Build and maintain data federation layers for lambda and Data Mesh architectures using tools like Starburst.
• Integrate AI techniques such as machine learning and natural language processing to automate processes and extract insights.
• Develop and deploy microservices-based architectures to support data-intensive applications while ensuring scalability and resilience.
• Ensure data quality, integrity, and security throughout the entire data lifecycle.
• Conduct feasibility studies, provide cost estimates, and perform systems analysis for new application development.
• Communicate complex technical concepts and solutions effectively to both technical and non-technical audiences.

What we're looking for

• Bachelor's degree in computer science, engineering, or a related field is required.
• Master's degree is preferred.
• 8+ years of experience in Big Data or enterprise large-scale application development using Databricks, Scala, Java, and Python.
• Minimum 5+ years of experience in a Data Engineering lead role focusing on Big Data, data federation, and data mesh architecture.
• Proficiency in at least one programming language such as Python, Java, or Scala.
• Expertise in designing and maintaining data pipelines using Hadoop, Spark, Hive, Kafka, and related ecosystems.
• Experience with ETL/ELT tools, microservices frameworks, and containerization technologies like Docker or Kubernetes.
• Practical experience applying AI/ML techniques to solve real-world problems and strong SQL skills for relational databases.