Lead System Analyst (Data Engineer Background)
āļāļĩāđāļāļāļēāļāļēāļĢāļāļĢāļļāļāļĻāļĢāļĩāļāļĒāļļāļāļĒāļē āļāļģāļāļąāļ (āļĄāļŦāļēāļāļ)What you'll do
- Lead System Analyst assigns to work on Finance-Risk and Compliance Data initiatives to support solution design and data integration between upstream applications, downstream applications, and business users.
- To design, build, and operate reliable data pipelines across batch, near-real-time, and real-time workloads.
- To utilize multiple technologies (e.g. Python, SQL/Stored Procedures, ETL/ELT tools) to ingest, transform, and deliver governed, audit-ready data.
- To orchestrate and monitor jobs, implement data quality controls, and ensure security, lineage, and observability, while modernizing existing workflows with automation, testing, and performance tuning.
- Build and maintain ingestion, transformation, and delivery pipelines that produce governed, audit-ready datasets.
- Use Python, SQL/Stored Procedures, and ETL/ELT frameworks (or any relevant technologies) to implement scalable and reusable data pipeline components.
- Orchestrate and monitor workloads (e.g., DAGs/schedulers), ensuring reliability, idempotency and rerun ability.
- Enforce data quality (completeness, validity, accuracy, timeliness, uniqueness) and reconciliation checks.
- Ensure security and compliance: access control, PII handling, encryption, and audit logging.
- Design and manage workflow orchestration for reliable execution, monitoring, and failure recovery with Airflow/Control-M/ESP (DAGs, retries, backfills, idempotency).
- Collaborate with Architects/Stewards to apply a Shared Canonical Model (CDM) and data standards.
- Implement security controls (RBAC/ABAC), PII masking, encryption in-transit/at-rest, and auditable logs.
- Maintain runbooks, technical specifications (e.g. data mapping), and contribute to CI/CD (Git, artifacts, release notes).
- Monitor pipelines (SLIs/SLOs), diagnose incidents, and drive continuous performance and cost improvements.
Promote data literacy and a data-driven culture through cross-functional collaboration.
Apply now if you have these advantages
- Bachelor's / Master degree in Computer Engineer, Computer Science, Information Technology, or related fields
- At least 8-12 years as System Analyst / Data Engineer, 2-3 years in banking industry.
- Strong background in one or more: large-scale data processing, data infrastructure engineering, or data modeling.
- Solid grasp of CDC patterns, schema-drift control, robust error handling, and recovery/replay.
- Proven track record improving pipelines via automation, testing, and performance tuning.
- Exposure to cloud data platforms (AWS/Azure/GCP), Databricks/Spark Structured Streaming is a plus.
- Proficient in Python and SQL (or any relevant programming languages) and be able to apply solid software engineering practices (testing, version control, code reviews).
- Strong SQL (complex queries, optimization) and Python (DB-API/pandas or PySpark) comfortable with Unix shell.
- Experience with one or more: Talend, IBM DataStage, Airflow, Kafka, Spark, Trino/Presto.
- Curious, resilient, and critical thinker, open to feedback and continuous improvement.
- Financial services, risk and regulatory data experience (e.g., IECC, IFRS9, Basel, BOT, AML, Credit Risk, Compliance) is an advantage.
Why join Krungsri?
- As a part of MUFG (Mitsubishi UFJ Financial Group), we a truly a global bank with networks all over the world.
- We offer a striking work-life balance culture with hybrid work policies (2 days minimum in office per week).
- Unbelievable benefits such as attractive bonuses, employee loan with special rates and many more.
** Apply now before this role is close. **
Stay connected with KRUNGRI CAREER at:
- FB: Krungsri Career(http://bit.ly/FacebookKrungsriCareer [link removed])
- LINE: Krungsri Career (http://bit.ly/LineKrungsriCareer [link removed])
Talent Acquisition Department
Bank of Ayudhya Public Company Limited
1222 Rama III Rd., Bangpongpang, Yannawa, Bangkok 10120
āļŦāļĄāļēāļĒāđāļŦāļāļļ āļāļāļēāļāļēāļĢāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāđāļĨāļ°āļāļ°āļĄāļĩāļāļąāđāļāļāļāļāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāļđāđāļŠāļĄāļąāļāļĢ āļāđāļāļāļāļĩāđāļāļđāđāļŠāļĄāļąāļāļĢāļāļ°āđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāđāļāđāļēāļĢāđāļ§āļĄāļāļēāļāļāļąāļāļāļāļēāļāļēāļĢāļāļĢāļļāļāļĻāļĢāļĩāļŊ
Remark: The bank needs to and will have a process for verifying personal information related to the criminal history of applicants before they are considered for employment with the bank.
Applicants can read the Personal Data Protection Announcement of the Bank's Human Resources Function by typing the link from the image that stated below.
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