Job title: Data Engineering Chapter Lead
Job type: Permanent
Emp type: Full-time
Salary type: Annual
Location: SG
Job published: 21 Jul 2022
Job ID: 32367
Contact name: Neil Matthams
Contact email: neil@functionn.io

Job Description

**Functionn is a sourcing partner of DKatalis**

Should you decide to apply for the below opportunity then the following process will apply:

  • Step 1: We will review your profile and if your experience is relevant we will arrange a introductory call to discuss your experience and the opportunity in more detail
  • Step 2: Should this introductory call go well then we will send your CV directly to the key decision-makers at DKatalis. There is no need to worry "if" your CV will be seen or reviewed. We guarantee that your CV will get in front of the right people. Quickly
  • Step 3: Should DKatalis feel that your skills and experience are relevant then they will reach out to you directly to start the interview process

It goes without saying that if you apply for this opportunity, but we feel you don't have the required skills / experience, then you will still receive a response from us explaining why we won't be arranging an introductory call

 

DKatalis are seeking an experienced data engineer to lead our data engineering chapter for data solutions. The data solutions teams build data pipelines to ingest and surface both batch and streaming data on GCP to support our team of data analysts, data scientists and various business stakeholders such as product engineering, growth, customer engagement, fraud, risk and compliance. 

The data engineering lead role will be responsible for ensuring alignment between data engineers across the various teams with respect to ensuring

  • best practices are defined and adopted

  • standardisation of tooling and processes where required

  • collaborating with data security team members to ensure the data solutions implement security best practices

  • continuous innovation happens

  • professional development is baked into the team’s way of working

  • data quality, data privacy, data discoverability, data lineage, consistency of data definitions and other data governance concerns are well understood and given priority when developing solutions.

  • assisting in growing the team in terms of quality and quantity

The data chapter lead will coordinate across the various data solutions teams’ engineering team leads as well as the data engineers within the teams themselves.

The candidate should have at least 7+ years experience, preferably 10 or more years though with at least 3 years leading a team.

Candidates should have experience across the following systems and languages:

  • Ideally GCP, but strong experience in another platform such as AWS or Azure will suffice

  • Cloud data warehouses such as BigQuery, Redshift or Snowflake

  • Knowledge of pub/sub systems such as Kafka

  • Data parallel processing frameworks like Spark or Flink on batch and streaming data

  • Workflow scheduler such as Apache Airflow

  • Experience programming in Scala and Python

  • Proficient in SQL

  • Comfortable writing detailed design documents

  • Working proficiency with Kubernetes

A solid understanding of the retail banking domain is desirable, but not required. 

 

 

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