Data Architect (Python, Spark, Databricks, Azure/AWS)
We are looking for a passionate Data Architect to join our team. As a Data Architect, you are responsible for designing, developing, and maintaining the data infrastructure for the customer's data science initiatives. This includes building data pipelines, data warehouses, and data lakes. Candidates should have a strong understanding of data engineering principles and practices, as well as experience with a variety of data technologies.
Top 3 reasons to join us
- Competitive salary and learning culture
- Excellent environment and team to help you grow
- Open, friendly, professional working environment, values-driven human
Your Role
- Design end-to-end data streams, storage, data serving systems and analytical workflows, including overall architecture, capabilities, platforms, tools, and governing processes.
- Build data pipelines to extract, transform, and load data from a variety of sources.
- Help define/improve best practices, guidelines and integration with other enterprise solutions
- Build data warehouses and data lakes to store and manage data.
- Develop and deploy data processing and analytics tools.
- Work with data scientists to develop and deploy data-driven solutions.
- Stay up to date on the latest data technologies.
- Provide direction to the Data Engineers and perform code review for them.
- Setting up metadata / master data structures to support the transformation pipelines built in Databricks.
- Strong fundamental knowledge of data structures and performance considerations.
What you bring?
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Machine Learning, Statistic, Data Science or other related technical disciplines.
- 5+ years of relevant experience in demonstrating a high degree of proficiency in designing and developing complex, high-quality big-data platforms serving analytical solutions
- Strong understanding of data engineering principles and practices.
- Experience with a variety of data technologies, such as Databricks, ADF (Azure Data Factory)
- Extensive experience with data modeling and designing/supporting both streaming and batch ETL pipelines
- Proficient in SQL/NoSQL.
- Strong programming proficiency using 1 or 2 of the following languages: Python, Scala.
- Experience with cloud computing platforms, such as AWS or Azure.
- Experience with big data technologies, such as Hadoop, Spark, Kafka, and Hive is a plus.
- Experience with BI tools like Tableau or Power BI is a plus.
- Ability to learn new technologies quickly.
- Ability to work independently and as part of a team.
- Excellent written and verbal communication skills.
- Data certifications (AWS Certified Data Analytics – Specialty, Azure Data Engineer Associate, GCP Professional Data Engineer, Databricks Data Engineer) are highly desirable.
Why EmeSoft?
- Receive your full salary during the probation period.
- Enjoy a 13th-month salary as an annual bonus.
- Benefit from annual salary reviews for potential increases.
- Comprehensive insurance coverage in line with Vietnamese labor law, plus premium healthcare.
- Company covers meal and parking allowances.
- Participate in exciting company outings, events, and team-building activities.
- Thrive in an open, friendly, and professional work environment with a values-driven, agile culture.
- Embark on an attractive career path with a strong focus on personal and professional development.
- Take advantage of sponsorship for training courses and professional certifications.
- Maintain a healthy work-life balance with a 40-hour work week, Monday through Friday.
How to apply?
If you’re ready to take the next step in your career, we’re eager to hear from you! Please send an email to talent.acquisition@emesoft.net with the job title you’re applying for and your latest resume attached. We’re looking forward to discovering how your skills and passions align with our team.
Don’t wait – your future starts today!
Join the EmeSoft team and elevate your career! We invite you to apply for our open positions and are excited to hear from you.
