Data Engineer

SAN0448

About Candidate

  • Expertise in designing and implementing scalable data pipelines for ingesting, transforming, and loading data using technologies such as PostgreSQL, Kafka, Airflow, dbt, and BigQuery.
  • Extensive experience in optimizing database performance, including indexing, query optimization, and replication for improved API responsiveness and data loading.
  • Strong knowledge in managing and maintaining cloud infrastructure using AWS and GCP, with expertise in Terraform for automated, consistent environments.
  • Proficient in implementing data quality improvements, such as Write-Audit-Publish (WAP) pattern, to reduce production bugs and enhance innovation cycles.
  • Skilled in leading and mentoring engineering teams, fostering collaboration, and ensuring alignment with organizational goals.
  • Led architecture design and development of self-service customer data platforms, streamlining global data integration and API services.
  • Expertise in implementing logging, data processing, and dashboard systems to enhance API observability.
  • Extensive experience in ML Ops, optimizing model training and deployment on Kubernetes, and achieving scalable solutions.
  • Expertise in designing and building data platforms with AWS stack (Glue, EMR, Athena) and reducing data processing costs through Spark job efficiency.
  • Focused on software engineering best practices including infrastructure as code, containerization, code review, CI/CD, and incident post-mortems.
  • Experienced in building and scaling engineering teams, fostering technical excellence, and driving adoption of modern architectures such as event-driven and cloud-native frameworks.
  • Strong background in establishing data governance, security, and self-service functionality for data scientists and analysts.
  • Proficient in mentoring teams and contributing to hiring processes by conducting coding and system design interviews.
  • Led the development and operation of early-stage products, taking them from conceptual stage to full production, and securing funding.
  • Expertise in full-stack development and cloud solutions, optimizing delivery speed and cost-efficiency.

Skills

Kafka, Airflow, dbt, BigQuery, PostgreSQL, Python, SQL, AWS, GCP, Kubernetes, Terraform, Spark, Flink, ML Ops, Java, Glue, EMR, Athena, Data Security, Continuous Integration, System Design, Full-Stack Development

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