Data Engineering Specialist

eCloudvalley Technology (Philippines), Inc; Taguig; On-site; PHP 781,200 - 1,004,400; Full time

Job summary

A technology consulting firm in Manila seeks a Data Engineering Specialist to design and implement data platforms. The role requires expertise in AI, cloud analytics, and data pipeline development. Candidates should have over 5 years of experience and a strong technical background. This position offers the opportunity to make a significant impact through innovative data solutions.

Qualifications

• Over 5 years of experience in data engineering and cloud data platform implementation.
• Extensive experience with AWS, Azure, or Google Cloud environments.
• Strong analytical skills to troubleshoot data workflows.

Responsibilities

• Design and implement end-to-end data platforms for AI and analytics.
• Oversee the implementation of cloud-based data platforms.
• Collaborate with customer teams to understand data needs.

Skills

AI and machine learning

Cloud-based analytics

Data pipeline development

Data architecture

Cross-functional collaboration

Problem-solving

Education

Bachelor’s degree in Computer Science

Tools

Apache Kafka

Apache Airflow

AWS Glue

Snowflake

AWS Redshift

Google BigQuery

Job description

We’re looking for passionate and experiencedData Engineering Specialistswho thrive on solving complex problems and unlocking the full potential of data for our customers. If you have a strong technical background in AI, machine learning, and cloud-based analytics platforms, this is an exciting opportunity to drive meaningful change in organizations through data-driven strategies.

In this role, you’ll partner closely with clients to design and implement cutting-edge AI and analytics solutions tailored to their unique needs. Your work will empower them to streamline business processes, make smarter decisions, and discover valuable insights hidden within their data.

• Customer Engagement:Collaborate closely with customer business and technical teams to understand their data needs and requirements, translating complex data challenges into effective pipeline solutions that drive successful outcomes.
• Analytics Platform Solutions Design:Design and implement end-to-end data platforms for AI and analytics, incorporating flexible data pipelines and appropriate data architectures for efficient data storage and access while incorporating robust security measures to protect sensitive information.
• Data Pipeline Development:Design and implement scalable data pipelines to ingest, process, and transform data from various sources into accessible formats for analysis, ensuring optimization for performance and reliability.
• Data Platform Implementation:Oversee the implementation of cloud-based data platforms (e.g., Snowflake, AWS Redshift, Google BigQuery) that enable seamless data storage, processing, and access while ensuring alignment with customer objectives.
• Cross-Functional Team Collaboration:Collaborate with various teams to understand their data requirements and provide the necessary infrastructure, tools, and support to enable successful analytics and AI initiatives.
• Documentation and Reporting:Maintain comprehensive documentation of data pipeline architectures, processes, and workflows. Regularly update stakeholders on project status, performance metrics, and challenges encountered during development.
• Continuous Improvement:Stay up to date with the latest trends in data engineering and cloud technologies. Identify areas for improvement in data pipelines and platforms, proposing innovative solutions to enhance performance and efficiency.

• Education:Bachelor’s degree in Computer Science, Information Technology, or a related field.
• Experience:Over 5 years of experience in data engineering, data pipeline development, and cloud data platform implementation, with extensive experience in environments such as AWS, Azure, or Google Cloud.
• Technical Expertise:Proficient in data pipeline tools and technologies (e.g., Apache Kafka, Apache Airflow, AWS Glue) and cloud-based data platforms (e.g., Snowflake, AWS Redshift, Google BigQuery).
• Analytical and Problem-Solving Skills:Strong ability to analyze data workflows and troubleshoot issues related to data ingestion, transformation, and integration.
• Communication:Excellent communication skills, with the ability to translate technical concepts into business value and work effectively with cross-functional teams.
• Self-Starter and Fast Learner:Ability to proactively lead tasks and projects with minimal supervision and adapt quickly to new technologies and evolving requirements