Collaborate with experienced data engineers, data analyst, data strategy consultant, and other stakeholders to understand intricate customer data requirements.
Design, implement, and maintain data infrastructure on Cloud to support our customer data architecture.
Develop, automate, optimize, and fine-tune data platform provisioning, scaling, and maintenance tasks to improve operational efficiency, performance, scalability, and cost-effectiveness.
Lead data pipeline design, development, and optimization, drawing on your expertise in data integration, ETL/ELT, modern tools, to ensure efficient data processing and cutting-edge solutions.
Implement data monitoring and alerting solutions while collaborating with DevOps teams to proactively identify and address data issues.
Ensure data security, compliance, and governance standards are met throughout the data platform, adhering to global data engineering standards and principles.
Establish and enforce global data engineering standards, ensuring strict adherence to data architecture, platform, quality, and governance principles.
Demonstrate your expertise in implementing data warehouse/lake solutions, data mesh architectures, and distributed processing technologies (e.g., Spark, Hadoop, Kafka) for production environments.
Showcase your advanced proficiency in SQL and relational/non-relational databases to optimize complex data queries and manipulations.
Exhibit mastery in programming languages such as Python, Shell scripting, and Scala/Java, leveraging them to develop sophisticated data platform engineering solutions.
Work hand-in-hand with cross-functional agile teams to architect and implement hybrid-cloud solutions with automated pipelines, ensuring seamless and high-performance data processing.
Act as a mentor and leader, providing guidance and mentorship to data engineers, fostering a collaborative and growth-oriented team culture.
Engage actively with the data engineering community, sharing insights, best practices, and innovative ideas to contribute to the growth of the industry.
Document data infrastructure design, configuration, and processes for reference and training purposes.
Job Title:
Data Platform EngineerJob Description:
Collaborate with experienced data engineers, data analyst, data strategy consultant, and other stakeholders to understand intricate customer data requirements.
Design, implement, and maintain data infrastructure on Cloud to support our customer data architecture.
Develop, automate, optimize, and fine-tune data platform provisioning, scaling, and maintenance tasks to improve operational efficiency, performance, scalability, and cost-effectiveness.
Lead data pipeline design, development, and optimization, drawing on your expertise in data integration, ETL/ELT, modern tools, to ensure efficient data processing and cutting-edge solutions.
Implement data monitoring and alerting solutions while collaborating with DevOps teams to proactively identify and address data issues.
Ensure data security, compliance, and governance standards are met throughout the data platform, adhering to global data engineering standards and principles.
Establish and enforce global data engineering standards, ensuring strict adherence to data architecture, platform, quality, and governance principles.
Demonstrate your expertise in implementing data warehouse/lake solutions, data mesh architectures, and distributed processing technologies (e.g., Spark, Hadoop, Kafka) for production environments.
Showcase your advanced proficiency in SQL and relational/non-relational databases to optimize complex data queries and manipulations.
Exhibit mastery in programming languages such as Python, Shell scripting, and Scala/Java, leveraging them to develop sophisticated data platform engineering solutions.
Work hand-in-hand with cross-functional agile teams to architect and implement hybrid-cloud solutions with automated pipelines, ensuring seamless and high-performance data processing.
Act as a mentor and leader, providing guidance and mentorship to data engineers, fostering a collaborative and growth-oriented team culture.
Engage actively with the data engineering community, sharing insights, best practices, and innovative ideas to contribute to the growth of the industry.
Document data infrastructure design, configuration, and processes for reference and training purposes.