Data Integration Associate

1 week ago

Bangkok, Bangkok, Thailand KASIKORN INVESTURE Full time ฿1,200,000 - ฿2,400,000 per year

Job Summary

We are looking for a proactive and detail-oriented Data Engineer to design, build, develop, and maintain robust data pipelines and data architecture. This role is crucial for ensuring that our organizational data is accurate, reliable, and readily available for analysis, reporting, and statistical/Machine Learning model development, specifically within the demanding financial services industry.

Key Responsibilities

  • Design and Develop Data Pipelines (ETL/ELT): Build and maintain data pipelines to ingest, transform, and load (ETL/ELT) both batch and real-time data from various internal and external sources (e.g., Core Banking Systems, Trading platforms, Customer data) into the Data Warehouse/Data Lake.
  • Manage Data Architecture: Contribute to the design of data models, schemas, and the overall Data Warehouse/Data Lake structure to ensure efficiency, standardization, and scalability to support business growth.
  • Ensure Data Quality & Integrity: Define and implement data quality checks, validation rules, and monitoring processes to ensure the accuracy, completeness, and reliability of data used for business decisions and regulatory reporting.
  • Cross-Functional Collaboration: Work closely with Data Scientists, Data Analysts, and Business Stakeholders to understand financial and business data requirements and translate them into effective technical data solutions.
  • Performance Optimization: Continuously optimize data pipelines, database queries, and data structures for performance, speed, and cost-efficiency.
  • Data Governance & Security: Support the implementation of data security, governance, and privacy policies in line with organizational and financial sector standards.

Required Qualifications and Experience

  • Professional Experience: Minimum of 2 - 3 years of hands-on experience as a Data Engineer or in a closely related data management role.
  • Financial Industry Experience: Prior experience or a solid understanding of data and business processes within a financial institution (e.g., Lending, Risk Management, Trading, Financial Reporting) is a significant advantage.
  • Technical Skills:
  • Strong proficiency in SQL for data manipulation and performance tuning.
  • Hands-on experience with a programming language, preferably Python or Scala, for data processing.
  • Experience with ETL/ELT tools and orchestration frameworks (e.g., Apache Airflow, dbt, Azure Data Factory, AWS Glue).
  • Familiarity with Data Warehouse technologies (e.g., Snowflake, Redshift, BigQuery) and/or Data Lake (e.g., S3, ADLS).
  • Basic knowledge of Cloud Platforms (AWS, Azure, or GCP).
  • Business Acumen:
  • Strong understanding of business objectives and the ability to translate commercial needs into technical data requirements.
  • Ability to see the bigger picture and the impact of data on business decision-making.
  • IT & Systems Knowledge:
  • Understanding of fundamental IT systems integration concepts, such as APIs, Microservices, and data extraction from various enterprise systems.

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