Lead Big Data Developer
1 week ago
Overview
Are you interested in building the next-generation platform that handles
petabytes of data
and powers
data insight creation
using cutting-edge
data science technologies
?
Are you excited about leveraging
Big Data
,
AI / Machine Learning
, and
Data Analytics
to deliver actionable insights?
We are a
dynamic team of top-notch engineers
dedicated to making a dent in the
FinTech universe
.
We're rapidly expanding in
Vancouver, beautiful British Columbia
, and if you wish to be part of this
Priceless experience
, read below.
The
Marketing Services (MS) Technology team
is looking for a
Senior Data Engineer
who is passionate about data and analytics, highly motivated, and capable of taking technical ownership of data solutions with an emphasis on
engineering efficiency
and
on-time delivery
.
The ideal candidate will be familiar with the fast-paced world of Big Data technologies and have experience building data solutions using
emerging tools
while ensuring
platform stability
. You'll work with diverse datasets and be at the forefront of transforming the way
Mastercard captures, processes, stores, and visualizes data
.
Role & Responsibilities
In this role, you will:
- Design and develop batch and streaming solutions
using various Big Data technologies. - Work closely with architects
to design secure, scalable, and efficient data platforms. - Take ownership of
assessing technologies and approaches
for data ingestion, transformation, and storage. - Develop software
utilizing open-source technologies to interface with distributed and relational data sources. - Collaborate with
cross-functional Mastercard teams
to identify functional and system requirements.
All About You
The ideal candidate for this position should have:
- Hands-on experience
with Big Data and analytics technologies, including
Hadoop
,
Spark
, and related frameworks. - Programming expertise
in
Java
,
Scala
, or
Python
, with a focus on developing data processing and transformation logic. - Real-time and batch data processing
experience, building robust data pipelines for real-time or near-real-time ingestion. - Proficiency in
data modeling
and
schema design
for both relational and non-relational databases, supporting high data volume and optimized query performance. - Exposure to
cloud technologies
with hands-on experience in
Databricks
and
Cloudera
, including knowledge of
cloud architecture
,
data security
, and
scalability best practices
. - Experience in
optimizing and managing ETL workflows
using scheduling, monitoring, and debugging tools. - Strong
problem-solving abilities
with a mindset for
automation and efficiency improvements
. - Excellent
communication and collaboration skills
to work effectively across technical and business teams, promoting knowledge sharing and alignment on data engineering best practices. - Proven track record of
delivering software projects
and a willingness to roll up your sleeves to get the job done. - Excellent oral and written communication skills.
- Familiarity with
Agile / Scrum methodologies. - Ability to
manage multiple priorities simultaneously. - A
BS/BA degree
in
Computer Science, Information Systems
, or a related field.
-
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