29 Panasonic Jobs

• Lead and mentor a team of data engineers in developing and managing scalable, secure, and high-performance data pipelines .
• Define best practices for data ingestion, transformation, and processing in a Lakehouse architecture .
• Drive automation, performance tuning, and cost optimization in cloud data solutions.

• Architect and manage AWS-based big data solutions (EMR, EKS, Glue, Redshift).
• Design and maintain Apache Airflow workflows for data orchestration.
• Optimize Spark and distributed data processing frameworks for large-scale workloads.
• Implement streaming solutions (Kafka, Kinesis, Flink) for real-time data processing.

• Collaborate with Data Scientists and AI/ML teams to build and deploy machine learning models using AWS SageMaker .
• Support feature engineering, model training, and inference pipelines at scale.
• Enable AI-driven analytics by integrating structured and unstructured data sources.

• Support BI and reporting teams with optimized data models for Amazon QuickSight and other visualization tools .
• Ensure efficient data aggregation and pre-processing for interactive dashboards and self-service analytics.
• Design, develop, and maintain middleware components that facilitate seamless communication between data platforms, applications, and analytics layers .

• Implement MDM strategies to ensure clean, consistent, and deduplicated data.
• Establish data governance policies for security, privacy, and compliance (GDPR, HIPAA, etc).
• Ensure adherence to data quality frameworks across structured and unstructured datasets.

• Partner with business teams, AI/ML teams, and analysts to deliver high-value data products .
• Define and maintain data architecture strategies aligned with business goals.
• Enable real-time and batch processing for analytics, reporting, and AI-driven insights.

Technical Expertise:

• Extensive AWS experience with services such as EMR, EKS, Glue, Redshift, S3, Lambda, and SageMaker.
• Proficient in big data processing frameworks (eg, Spark, Hive, Presto) and Lakehouse architectures.
• Skilled in designing and managing Apache Airflow workflows and other orchestration tools.
• Solid understanding of Master Data Management (MDM) and data governance best practices.
• Proficient with SQL & NoSQL databases (eg, Redshift, DynamoDB, PostgreSQL, Elasticsearch).
• Middleware Development Proven expertise in building middleware components like REST API that integrate data pipelines with applications, analytics platforms, and real-time systems.
• Hands-on experience with Gitlab CI/CD, Terraform, CFT, and Infrastructure-as-Code (IaC) methodologies.
• Familiarity with AI/ML pipelines, model deployment, and monitoring using SageMaker.
• Experience with data visualization tools, particularly AWS QuickSight, for business intelligence.

• Bachelor s degree or higher (UG+) in Computer Science, Data Engineering, Aerospace Engineering, or a related field.
• Advanced degrees (Master s, PhD) in Data Science or AI/ML are a plus