Principal Data Engineer

5 days ago


Singapore DKatalis Full time

**About DKatalis**

DKatalis is a financial technology company with multiple offices in the APAC region. In our quest to build a better financial world, one of our key goals is to create an ecosystem linked financial services business.

DKatalis is built and backed by experienced and successful entrepreneurs, bankers, and investors in Singapore and Indonesia who have more than 30 years of financial domain experience and are from top-tier schools like Stanford, Cambridge London Business School, JNU with more than 30 years of building financial services/banking experience from Bank BTPN, Danamon, Citibank, McKinsey & Co, Northstar, Farallon Capital, and HSBC.

**About the role**

We are seeking an experienced data engineer to advise, mentor and give hands-on support to our data engineers working across multiple teams in different business areas. 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 stakeholders such as product engineering, growth, customer engagement, fraud, risk and compliance.

The principal data engineer will be responsible for ensuring alignment between data engineers across the various teams with respect to ensuring:

- Best practices are defined and adopted, using visible metrics where required to help drive desired outcomes
- New solutions are designed with strong architectural foundations
- 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.
- Decisions on whether balance to deploy open source solutions, build internal solutions or buy vendor software are made in a balance context-aware manner considering the long term impact on the organisation and teams
- Solid culture around dataops is cultivated
- Ongoing collaboration with security team members
- Standardisation of tooling and processes is performed where required
- Continuous innovation happens
- Professional development is baked into the team's way of working
- Assistance in growing the team in terms of quality and quantity

**What you will need to have**

The principal data engineer will coordinate across the various data solutions teams' engineering team leads as well as the data engineers within the teams themselves.
- Ideally **GCP**, but strong experience in another platform such as AWS or Azure will suffice
- Cloud data warehouses such as BigQuery, Redshift or Snowflake
- Familiarity with dbt
- 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
- Familiarity with data quality tools such as Great Expectations or using dbt to drive dat quality
- Proficiency 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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