Data Engineer, Sg

2 weeks ago


Singapore JERA Global Markets Pte. Ltd. Full time

COMPANY DESCRIPTION

About the Company
JERA Global Markets (JERAGM) is a leading utility-backed seaborne energy trader specialising in LNG, coal and freight. A joint venture between majority shareholder JERA Co., Inc. and EDF Trading, JERAGM's shareholders are among the world's largest utilities.


JERAGM operates one of the largest energy portfolios in the world which gives it an in-depth understanding of the way local, regional and international energy markets behave.

These insights enable it to help its customers increase security of supply, optimise their portfolios and improve the risk management of their assets.


JERAGM LNG team manages the flexibility of over 35 million tonnes of supply each year, with structural access to both the European and North American gas markets.

The coal team manages 60 million tonnes of supply each year for its shareholders and third-party customers and operates a major coal terminal in the Netherlands.


Headquartered in Singapore, JERAGM has a global talent pool of more than 250 people across offices located in four strategic locations: Singapore, Japan (Tokyo), the UK (London) and the US (Baltimore).

JERAGM is strongly capitalised with over US$500 million in paid up capital and a total equity of US$3 billion. JERAGM has retained its A+ Stable rating from R&I, attributable to a robust business model and solid financial base.

DESIGNATION :
Data Engineer, SG

RESPONSIBILITIES

Position Description:

The Data Engineer is a software development role within the Data Team in the JERAGM IT Department.


JERAGM is making a strategic investment in Data and Analytics to enable a more data driven approach to commercial decision making, risk management and operations.

As part of this, the Data Team is leading delivery of a modern data platform using Azure services and Databricks.

The team is near the beginning of a broad and complex programme of work delivering new capabilities across the business, including:

  • A central warehouse of near realtime trade, valuation and risk data
  • A central hub for sharing realtime prices and analytics
  • Pipelines for scraping, analysing and visualising market prices and fundamental data
  • Processes and tools for data governance and discovery
The Data Engineer will be part of a highly qualified team, primarily based in Singapore. The team operates an agile delivery framework in a fast-paced trading environment following DevOps principles and practices. The team believe in the mantra of "acting fast, failing fast and learning fast". Every team member is hands-on and team members are encouraged to work closely with each other and end users.

Everyone in the team is highly engaged and we continually share our thoughts and ideas in daily stand ups and weekly system design meetings.

At the same time as collaborating as a team, we encourage our Engineers to plan and execute their own work so they can work autonomously and take ownership of their work.


The role will cover the following:

  • Designing and delivering software using an agile and iterative approach based on Scrum or Kanban
  • Following and contributing to improvement of JERAGM software engineering practices e.g., source code management, testdriven development, automated testing, CI/CD
  • Supporting the Lead Data Engineer in technical architecture and design
  • Building an understanding of how data is used within JERAGM's commercial activity, and using this knowledge when working with Business Analysts or users to identify system requirements
  • Analysing and estimating IT changes giving input on technical opportunities, constraints, and tradeoffs
  • Creating documentation and presenting to technical and nontechnical audiences
  • Providing handover to Support teams and providing third line support for short periods after releases

QUALIFICATIONS

Experience Required:

  • Extensive technical knowledge and experience (5+ years) of:
  • Technologies:
  • SQL Server database design and development (SQL, relational and dimensional modelling)
  • Analytical querying using technologies such as SSAS cubes or columnar data stores
  • ETL tools such as SSIS, Alteryx, Azure Data Factory
  • Building data pipelines using code e.g. Pyspark
  • Modern cloudbased data architectures and technologies such as Data Lake, Delta Lake, Data Lakehouse e.g. Azure Data Lake Gen 2, Azure Delta Lake
  • Lakehouse architecture using Databricks, Hudi or Iceberg
  • NoSQL using CosmosDB, MongoDB, DynamoDB etc.
  • Python scripting, including data engineering and machine learning libraries
  • Scripting languages such as powershell, bash, DAX, Mlanguage etc. Note
  • We primarily use SQL, Pyspark and Python in our daytoday work along with some coding around DAX, Bash, Powershell and other scripting languages.
  • Distributed computing mainly around Spark
  • Big data files formats e.g. Parquet, Avro, ORC etc.
  • Big data technologies such as Hadoop, Hive, Map-Reduce, Partition design, performance tuning in Spark etc.
  • Reporti

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