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Daulfin Grey HR Pte Ltd

Open 30d reposted 2× · 2 open copies

Data Engineer

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Summary

Data Engineer on SGX's Data & Analytics team (posted via Daulfin Grey HR): begins with a 6-month Finance department attachment producing reports and analysis, then builds scalable ETL pipelines and data platforms for finance and market data, supporting KDB+ and Snowflake warehouses. Core stack: Python, Snowflake, AWS, Tableau, SAP.

Data & Analytics Team

The Data & Analytics team aims to leverage SGX’s valuable data assets to drive the creation of insights and data-driven decisions to solve business and corporate challenges. We ingest, curate, and analyze data that is critical to the organization, and build data platforms and infrastructure to democratize the data. As a team, we strive to realize the value of our data assets to drive data-driven decisions and innovative data-centric solutions.

Job Description

We are seeking a Data Engineer with a passion for working with data and engineering, with a key focus on Finance-related data in a Stock Exchange environment. This role will start with a finance focus, including a 6‑month attachment to the Finance department for immersion of finance domain knowledge, and thereafter return to the Data Engineering team within the Data & Analytics team. Key focus is to work on Finance-related use cases but not limited to this.

During the attachment with the Finance department, you will produce regular reports and perform analysis using financial data for leadership review, and work collaboratively across the entire finance team to analyse SGX’s business performance and strategy. Upon returning to the Data Engineering team, you will focus on data engineering for finance-related data with a secondary focus on market (securities/derivatives) related data and adoption of cloud setup as part of the ETL pipeline.

Responsibilities
  • Design, build and deploy data solutions that can handle the needs of the data products and users across the organization.
  • Build scalable and reliable ETL pipelines and processes to ingest data from multiple sources and create curated layers for users to self‑help to the data.
  • Design and secure data in different states (e.g. at rest/in transition/on cloud).
  • Work with users closely to understand their needs and propose a viable solution.
  • Identify and drive process improvements, including the creation of standard and ad‑hoc reports, tools, and dashboards.
  • Support enterprise data warehouse including on‑prem data warehouse running on KDB+ and modern high‑performance native cloud data warehouse (Snowflake).
  • Provide support for data‑related queries and discrepancies.
  • Identify and drive process improvements.
  • Stay abreast of and analyze industry developments to identify areas of continuous improvements.
  • Provide technical coaching and guidance to junior members of the team.
Requirements
  • Bachelor's Degree in Computer Science, Computer Engineering or equivalent.
  • 2-4 years of relevant working experience in data engineering roles.
  • Analytical, passionate about data, and possess an eye for details.
  • Strong troubleshooting skills and ability to react quickly to resolve issues.
  • Hands‑on competency in Python and/or other programming languages.
  • Experience/knowledge in Snowflake and/or AWS is preferred.
  • Experience/knowledge in Corporate Finance and/or SAP is a plus.
  • Experience/knowledge in Tableau is a plus.
  • Strong communication skills and good team player, with the ability to interact with business users, technical colleagues, and vendors.
  • Able to think up innovative ideas to solve problems and challenges.

Skills

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See also

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