Data Engineer BI Developer, Python, Cloud

ABOUT DATATYK:

At Datatyk, we believe that data is the foundation of smart decisions and successful strategies. We focus on providing powerful and innovative data analytics solutions that help our clients turn data into valuable insights. We provide advanced Data & AI solutions to help our clients gain a competitive edge. If you are passionate about data technology and developing Data & AI solutions, join us to build groundbreaking solutions together!

JOB DESCRIPTION:

We are seeking a talented Data Engineer (BI Developer) to join our team. You will be responsible for designing, developing, and maintaining the data platform system. You will work with both internal and Client teams to ensure data is prepared and delivered in the most optimal way for business decisions.

KEY RESPONSIBILITIES:

• Build Data Platform Solution: Collect, process, and standardize data from various sources into a centralize data platform
• Build and Maintain Data Warehouses: Develop and maintain data warehouses and ETL (Extract, Transform, Load) systems to ensure data accuracy and availability.
• Optimize Performance: Optimize BI system performance and data processes to ensure fast response times and high efficiency.
• Data Integration: Work with various data sources to integrate and consolidate data, ensuring data quality and integrity.
• Technical Support and Training: Provide technical support and training for teams and end-users on BI tools and reporting.

Experience: Minimum of 1-2 years of experience as a Data Engineer, BI Developer, or similar role, with practical experience in developing BI solutions and managing data.

Technical Skills:

1/ Core Technical Skill:

• Cloud Platforms Proficiency: Candidate should be required one of these working experienced
• Azure: Knowledge of Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory for data integration and ETL tasks, and Azure Databricks for big data processing, Microsoft Fabric
• AWS: Familiarity with services like Amazon S3 (storage), Amazon Redshift (data warehousing), AWS Glue (ETL processes), and AWS Lambda (serverless computing) is crucial.
• Databricks: Proficiency in using Databricks for big data processing and analytics. This includes understanding how to use Apache Spark within Databricks for data transformation and machine learning tasks
• Data Modeling and Database Management:
  • Strong understanding of both SQL and NoSQL databases.
  • Experience with data warehousing solutions and optimizing databases for performance and scalability
• Data Integration and ETL Processes:
  • Proficiency in designing and managing ETL pipelines to integrate data from various sources
• Programming Skills:
  • Proficiency in languages like Python, Spark notebook, or Scala for data manipulation and automation
• Additional Skills
  • Data Security and Compliance:
  • Understanding of data governance, security best practices, and compliance requirements.
  • DevOps and Automation:
  • Familiarity with CI/CD pipelines
  • Machine Learning and Analytics:
  • Basic knowledge of machine learning principles and tools for data analysis.

2/ Soft Skills:

• Strong problem-solving abilities, effective communication, and teamwork skills.
• Strong analytical and problem-solving skills with the ability to optimize system performance and processes.
• Excellent communication skills with the ability to work effectively with both technical and non-technical teams.
• Excellent presentation skills with the ability to explain complex issues clearly and understandably.

Education:

• Bachelor's degree in a related field such as Computer Science, Engineering, Mathematics, or equivalent.

Personal Development:

• Opportunities for career growth through training and hands-on projects.
• Support the cost of taking international professional certificates.

Attractive Benefits:

• Competitive compensation package including health insurance, paid leave, and other benefits.
• Performance review yearly.
• 13rd months salary
• Teambuilding, Company trip, Tea break, Knowledge-sharing.

Flexible Work:

• Flexible working policies.
• Working time: Monday - Friday, 9:00AM - 06:00 PM.
• 16 vacation days/year and statutory holidays including Christmas.