Senior Data Engineer (Nghỉ T7-CN | GIMO Care | 100% Lương Thử Việc)
Hạn nộp hồ sơ: 26/11/2026 (Còn 29 ngày)
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About the Role
You will design, build, and operate Gimo's lakehouse-based Data Platform end-to-end. From ingesting operational data out of MySQL, BigQuery, SharePoint, Jira, and external sources; through the data transformation layers on Amazon S3; into Amazon Redshift, DuckDB, and other downstream consumers.
You will work closely with Data Analysts, Product Owners, Risk, Operations, and Growth teams to turn raw operational data into reliable, well-modeled, timely datasets that the whole company can trust.
Key Responsibilities
Ingestion & CDC: Build and operate data pipelines that ingest data from multiple sources (Amazon Aurora, AWS RDS, GCP BigQuery, SharePoint, Jira, and other 3rd party services).
Lakehouse Storage: Manage layered lake houses on Amazon S3.
Transformation & Modeling: Develop dbt models based on Kimball's Dimensional Modeling Techniques.
Orchestration: Author and maintain Apache Airflow pipelines on the self-hosted EC2 cluster, using the in-house DAG factory pattern to generate ingestion, transformation, and export DAGs. Coordinate dependencies across Lambda, ECS dbt, DuckDB, Redshift, and SageMaker; manage retries, SLAs, and recovery.
Data Warehouse: Operate the dual warehouse setup. Amazon Redshift for large-scale analytics and Power BI reporting; DuckDB for near real-time operational dashboards in Metabase. Tuning workloads on both Redshift and DuckDB to optimize performance and cost.
Serving & Consumption: Deliver curated datasets to downstream BI tools (Metabase ,Power BI), alerts and reports services (Lark, Teams, and Email), and external services (MoEngage).
Data Governance & Catalog: Maintain the Data Catalog (AWS Glue Data Catalog, DataHub).
Reliability, Cost & Observability: Monitor pipeline freshness, volume, and data quality; instrument alerts through Lark; run postmortems; identify and remove single points of failure; optimize S3 / Lambda / Redshift, and other related services cost.
Platform Optimization: Continuously improve accuracy, scalability, performance, and reliability of the platform; contribute to modernization efforts
Mức độ phù hợp và xếp hạng của bạn so với ứng viên khác như thế nào?
About the Role
You will design, build, and operate Gimo's lakehouse-based Data Platform end-to-end. From ingesting operational data out of MySQL, BigQuery, SharePoint, Jira, and external sources; through the data transformation layers on Amazon S3; into Amazon Redshift, DuckDB, and other downstream consumers.
You will work closely with Data Analysts, Product Owners, Risk, Operations, and Growth teams to turn raw operational data into reliable, well-modeled, timely datasets that the whole company can trust.
Key Responsibilities
Ingestion & CDC: Build and operate data pipelines that ingest data from multiple sources (Amazon Aurora, AWS RDS, GCP BigQuery, SharePoint, Jira, and other 3rd party services).
Lakehouse Storage: Manage layered lake houses on Amazon S3.
Transformation & Modeling: Develop dbt models based on Kimball's Dimensional Modeling Techniques.
Orchestration: Author and maintain Apache Airflow pipelines on the self-hosted EC2 cluster, using the in-house DAG factory pattern to generate ingestion, transformation, and export DAGs. Coordinate dependencies across Lambda, ECS dbt, DuckDB, Redshift, and SageMaker; manage retries, SLAs, and recovery.
Data Warehouse: Operate the dual warehouse setup. Amazon Redshift for large-scale analytics and Power BI reporting; DuckDB for near real-time operational dashboards in Metabase. Tuning workloads on both Redshift and DuckDB to optimize performance and cost.
Serving & Consumption: Deliver curated datasets to downstream BI tools (Metabase ,Power BI), alerts and reports services (Lark, Teams, and Email), and external services (MoEngage).
Data Governance & Catalog: Maintain the Data Catalog (AWS Glue Data Catalog, DataHub).
Reliability, Cost & Observability: Monitor pipeline freshness, volume, and data quality; instrument alerts through Lark; run postmortems; identify and remove single points of failure; optimize S3 / Lambda / Redshift, and other related services cost.
Platform Optimization: Continuously improve accuracy, scalability, performance, and reliability of the platform; contribute to modernization efforts
Yêu cầu
Must to have:
Educational Background: Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field.
SQL: Advanced SQL like window functions, CTEs, MERGE/UPSERT, query tuning, etc. Comfortable with at least one columnar warehouse dialect (Redshift, BigQuery, Snowflake, or DuckDB).
Programming: Solid Python for data engineering. Experience writing production-grade ETL/ELT code, not just notebook scripts.
AWS Data Stack: Hands-on experience with Amazon S3, AWS Lambda, Amazon Redshift, IAM, and CloudWatch. Comfortable operating serverless pipelines and reasoning about Lambda limits.
Orchestration: Practical experience with Apache Airflow like DAG authoring, Operators, XCom, retries, SLAs, and troubleshooting scheduler / worker issues.
Pipeline Design: Proven experience designing and building ETL / ELT pipelines, CDC ingestion, and dimensional data models.
Data Warehouse Concepts: Solid understanding of columnar storage, partitioning, distribution/sort keys, and the lakehouse pattern (Raw / Standardized / Curated).
Data Governance & Security: Working knowledge of information security principles, PII handling, access control, and data retention policies.
Ways of Working: Comfortable with Git-based workflows, code review, on-call rotation, incident response, and writing clear documentation.
Nice to have:
Hands-on experience with dbt.
Experience with DuckDB (embedded analytics, Parquet/S3 querying, micro-batch pipelines).
Familiarity with GCP BigQuery and Google Firebase Analytics.
Familiarity with AWS Glue Data Catalog, Redshift Spectrum, or Amazon Athena.
Familiarity with AWS SageMaker batch inference and ML data pipelines for credit scoring.
Some hands-on building reports with BI tools like Metabase and/or Power BI.
Experience with customer engagement platforms (MoEngage, Braze, CleverTap).
Experience scraping / integrating external sources via requests or Selenium.
BENEFIT
Impact-Driven Work: Be part of a mission-driven fintech company that is transforming financial access for millions of underserved Vietnamese workers. The data you engineer directly powers credit decisions, disbursement, and customer engagement.
Modern Data Stack: Work on a real production lakehouse that integrate Open-table format, dbt, DuckDB, Redshift, SageMaker and get ownership over meaningful parts of the platform.
Growth Opportunities: Work in a fast-growth environment that values autonomy, accountability, and empowering individuals to take initiative and make decisions.
Innovative Culture: Join a team that embraces experimentation, data, and technology to drive solutions, and encourages collaboration to challenge the status quo.
Compensation & Benefits: Competitive salary, performance bonus, Gimo Care health insurance, free parking, annual salary review, minimum of 13 months' salary per year, and 100% salary paid during the probationary period and other benefits.
How to apply
If you are excited to kickstart your HR career with us, send your CV with the subject line: [Job position Application - Your Name].
We look forward to having you on board and growing together at Gimo!
Educational Background: Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field.
SQL: Advanced SQL like window functions, CTEs, MERGE/UPSERT, query tuning, etc. Comfortable with at least one columnar warehouse dialect (Redshift, BigQuery, Snowflake, or DuckDB).
Programming: Solid Python for data engineering. Experience writing production-grade ETL/ELT code, not just notebook scripts.
AWS Data Stack: Hands-on experience with Amazon S3, AWS Lambda, Amazon Redshift, IAM, and CloudWatch. Comfortable operating serverless pipelines and reasoning about Lambda limits.
Orchestration: Practical experience with Apache Airflow like DAG authoring, Operators, XCom, retries, SLAs, and troubleshooting scheduler / worker issues.
Pipeline Design: Proven experience designing and building ETL / ELT pipelines, CDC ingestion, and dimensional data models.
Data Warehouse Concepts: Solid understanding of columnar storage, partitioning, distribution/sort keys, and the lakehouse pattern (Raw / Standardized / Curated).
Data Governance & Security: Working knowledge of information security principles, PII handling, access control, and data retention policies.
Ways of Working: Comfortable with Git-based workflows, code review, on-call rotation, incident response, and writing clear documentation.
Nice to have:
Hands-on experience with dbt.
Experience with DuckDB (embedded analytics, Parquet/S3 querying, micro-batch pipelines).
Familiarity with GCP BigQuery and Google Firebase Analytics.
Familiarity with AWS Glue Data Catalog, Redshift Spectrum, or Amazon Athena.
Familiarity with AWS SageMaker batch inference and ML data pipelines for credit scoring.
Some hands-on building reports with BI tools like Metabase and/or Power BI.
Experience with customer engagement platforms (MoEngage, Braze, CleverTap).
Experience scraping / integrating external sources via requests or Selenium.
BENEFIT
Impact-Driven Work: Be part of a mission-driven fintech company that is transforming financial access for millions of underserved Vietnamese workers. The data you engineer directly powers credit decisions, disbursement, and customer engagement.
Modern Data Stack: Work on a real production lakehouse that integrate Open-table format, dbt, DuckDB, Redshift, SageMaker and get ownership over meaningful parts of the platform.
Growth Opportunities: Work in a fast-growth environment that values autonomy, accountability, and empowering individuals to take initiative and make decisions.
Innovative Culture: Join a team that embraces experimentation, data, and technology to drive solutions, and encourages collaboration to challenge the status quo.
Compensation & Benefits: Competitive salary, performance bonus, Gimo Care health insurance, free parking, annual salary review, minimum of 13 months' salary per year, and 100% salary paid during the probationary period and other benefits.
How to apply
If you are excited to kickstart your HR career with us, send your CV with the subject line: [Job position Application - Your Name].
We look forward to having you on board and growing together at Gimo!
Quyền lợi
Thưởng
performance bonus
minimum of 13 months' salary per year
Chăm sóc sức khoẻ
Gimo Care health insurance
Xe đưa đón
free parking
Xem thêm
performance bonus
minimum of 13 months' salary per year
Chăm sóc sức khoẻ
Gimo Care health insurance
Xe đưa đón
free parking
Xem thêm
Thông tin khác
NGÀY ĐĂNG
26/10/2026
CẤP BẬC
Nhân viên
NGÀNH NGHỀ
Công Nghệ Thông Tin/Viễn Thông > Data Engineer/Data Analyst/AI
KỸ NĂNG
Access SQL, Python For Data Engineering, Apache Airflow, AWS Services, Collaboration
LĨNH VỰC
Tài Chính
SỐ NĂM KINH NGHIỆM TỐI THIỂU
5
QUỐC TỊCH
Không hiển thị
Xem thêm
26/10/2026
CẤP BẬC
Nhân viên
NGÀNH NGHỀ
Công Nghệ Thông Tin/Viễn Thông > Data Engineer/Data Analyst/AI
KỸ NĂNG
Access SQL, Python For Data Engineering, Apache Airflow, AWS Services, Collaboration
LĨNH VỰC
Tài Chính
SỐ NĂM KINH NGHIỆM TỐI THIỂU
5
QUỐC TỊCH
Không hiển thị
Xem thêm
Thông tin chung
- Thu nhập: Thương lượng
Nơi làm việc
- 10th floor, ADG Tower, 37 Le Van Thiem, Nhan Chinh, Thanh Xuan, Hanoi
Việc làm tương tự khác
Công ty Cổ phần Gimo
Xem trang công ty- Địa chỉ công ty: Toà nhà ADG, số 37 Lê Văn Thiêm, phường Thanh Xuân, thành phố Hà Nội.
- Quy mô: Từ 26 - 100 nhân viên
- Lĩnh vực: Ngân hàng/ Tài Chính
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