All right, all right - let’s cut to the formalities. Here's the deal. At Hollard, we get up in the morning to ensure people sleep better at night. Our job is to look after the stuff our customers love. In fact, 5 million people already trust us with their stuff. That's pretty big deal to us.
Senior Cloud Data Engineer
Required Knowledge and Experience
Your duties & responsibilities
- Reporting to the
Data Engineer Practice Manger your key focus areas will be:
- You will be
required to design, build, and support the delivery of modern data
engineering solutions in the Azure data platform, collaborating closely
with cross-functional teams within Hollard, including the Infrastructure
DevOps team, solution architects, subject matter experts, data modelers,
etc. This collaboration aims to ensure that Hollard’s data platform
ecosystem is optimal in supporting business needs. Additionally, you will
work collaboratively with vendors to ensure that data engineering delivery
and practices meet Hollard’s standards.
Your duties and responsibilities include:
- Maintain,
support, and monitor existing production Azure Synapse data engineering
pipelines, PySpark notebooks, data platform lake house architecture and
Azure SQL ODS storage and Stored Procedures, CICD pipelines to make sure
all data loads on data platform meet data quality standards and business
SLA requirements.
- Participate and
contribute to Azure data platform architecture design, data modelling,
gathering and analysis of data requirements; understand document,
communicate and, build appropriate solutions.
- Participate,
design, build, deliver, and document data platform related projects with
latest Azure data analytics technologies.
- Promote data
engineering best practices with CICD YAML pipelines and automation.
- Coach and mentor
junior data engineers on Azure technologies.
- Knowledge
acquired awareness, skills and/or expertise
- 10+ year
demonstrable experience in design, build and support of data engineering
pipelines in the data warehousing, BI analytics, and/or ML space,
including 5+ year work experience using Azure data analytics tool such as
Data Factory, Synapse, Azure SQL, data lake gen2, key vault.
- Strong knowledge
and extensive experience in implementing modern lake house architecture on
Azure Data Lake Gen2 and Apache Spark using PySpark.
- Strong knowledge
and experience in metadata driven data engineering pipeline design and
development towards reusable patterns and frameworks.
- Strong data
modelling knowledge and physical implementation experiences with
Dimensional and/or Data Vaults methodologies.
- Strong knowledge
and extensive experience in working in an Agile framework with CI/CD using
modern DevOps / Data Ops integrated processes with YAML pipelines
- Knowledge of
machine learning, MLOps, AI is desirable
- Knowledge of IaC
such as BICEP and/or Terraform is desirable
- Experience of
manipulating semi-structured data (XML, JSON)
- Behavioural
Competencies personal qualities
- Be available and
engaged, flexible and resourceful with a can-do attitude.
- Passion for
continuous learning with curiosity for technology and analytics
- Excellent
communicator, collaborator and “people person” with an ability to build
rapport quickly.
- Ability to
effectively manage challenging situations without loss of focus when under
pressure.
- Be comfortable
with ambiguity and willing to get outside of comfort zone while delivering
tangible results.
Educationa Requirements
- Bachelor’s or
Master’s degree in Computer/Data Science Technical or related field is a
must. Post-graduate is highly regarded.
- Microsoft Azure
Data Engineering Associate (DP-203) certification.
Method of
Application
Interested and qualified? Go to Hollard Insurance to apply