As our Data Analytics Engineer, you will play a pivotal role in designing and implementing our analytics infrastructure, ensuring that data is reliable, accessible, and actionable. Your expertise will directly influence critical business decisions and shape how FPT Digital leverages data to drive innovation and growth.
Responsibilities
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Data Architecture & Modeling:
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Design, build, and maintain robust data systems utilizing Delta Lake and Lakehouse architectures.
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Apply core principles of Data Modeling, Data Warehouse, Data Lake, and Lakehouse frameworks to ensure scalable and efficient data storage and retrieval.
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Pipeline Development (ETL/ELT):
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Design and implement automated, high-performance ETL/ELT pipelines to ingest, transform, and clean large-scale datasets from disparate sources.
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Leverage Python and PySpark to develop and optimize distributed data processing jobs.
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Data Operations & Platform Optimization:
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Establish frameworks for Data Quality, Monitoring, Logging, Retry mechanisms, and Alerting to ensure pipeline reliability and minimize downtime.
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Proactively monitor and optimize system performance and cloud costs (Performance & Cost optimization) across the data platform, specifically within Databricks.
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Cross-Functional Collaboration:
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Partner closely with Data Analysts (DA), Business Analysts (BA), and Data Scientists (DS) to translate complex business requirements into production-ready data assets.
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Qualifications & Requirements
- 3+ years of experience as an Analytics Engineer, Data Engineer, or a closely related role.
- Expertise in SQL, including complex queries, performance optimization, and data transformation.
- Strong background in data modeling, including dimensional modeling and analytics engineering best practices.
- Experience in dashboard development and data visualization using BI tools such as Looker, Mode, Hex, or similar.
- Previous experience in a fast-paced, high-growth environment with the ability to adapt and scale analytics solutions.
- Self-starter mindset, capable of independently driving projects from concept to execution with minimal supervision.
Bonus Skills
- Experience with dbt, including building and maintaining analytics workflows.
- Proficiency in Python for data processing and automation.
- Experience with Snowflake administration, performance tuning, and optimization.
- Familiarity with Databricks and cloud-based data platforms.
- Previous experience as an early-stage Analytics Engineer in a high-growth startup or consulting environment.
- Opportunity to work with leading experts in digital transformation and AI.
- Exposure to cutting-edge technology and innovative projects across industries.
- Collaborative and dynamic work environment with opportunities for career growth.
- Competitive salary and performance-based incentives.
- Access to ongoing learning and development programs.
