About the Role

As an Expert Data Engineer, you will be part of a cross-functional development team dedicated to building innovative, scalable data solutions that drive tomorrow's experiences. You will design and maintain large-scale data infrastructure, work closely with analysts and data scientists, and contribute to internal technical communities.

Responsibilities

Build, deploy, and maintain mission-critical analytics solutions for processing large-scale data.
Develop components for data ingestion, real-time streaming, batch processing, and ETL across various storage platforms.
Own parts of the engineering infrastructure; improve platform quality, performance, and maintainability.
Collaborate with other engineers to share knowledge and continuously learn new technologies.
Ensure solutions meet requirements for functionality, scalability, reliability, and availability.
Support end-to-end solutions, performing development, QA, and DevOps roles as needed.
Partner with business analysts and data scientists to understand and support use cases.
Participate in unit activities, conferences, and promote best practices.
Contribute to sales efforts, customer meetings, and digital services engagement.

Requirement

Technical Experience

5+ years of experience coding in SQL, Java, Python, or Scala, with solid computer science fundamentals.
3+ years of experience leading production deployments of large-scale backend data systems.
2+ years of hands-on experience with tools like Hadoop, MapReduce, Pig, Hive, Impala, Spark, Kafka, Storm, and databases like HBase, Cassandra.
3+ years working with cloud data platforms: AWS, Azure, or GCP.

Data Engineering Expertise

Strong knowledge of Data Governance, including data quality, security, and compliance standards.
Deep understanding of Data Warehousing design, optimization, and implementation.
Experience with SQL and MPP databases (e.g., Vertica, Netezza, Greenplum).
Familiarity with data quality testing, automation, and visualization tools.
Experience in BI report and dashboard design (e.g., Power BI, Tableau).

Engineering Practices

Experience with Agile methodologies (e.g., SCRUM).
Strong grasp of the software development lifecycle, including coding standards, version control, code reviews, CI/CD, and operations.
Proven ability to lead development teams: managing backlogs, peer review processes, and maintaining development standards.

Education

Bachelor's degree in Computer Science or Engineering from a top-tier university; Master's preferred.

Desirable Skills

Experience in data science or machine learning projects.
Proficiency in backend development and deployment.
Knowledge of CI/CD pipelines and related tools.
Understanding of enterprise-level data analytics.
Experience with platforms like Databricks, Snowflake.
Familiarity with Kubernetes and container orchestration.