roles, warehouses, dynamic tables, streams, tasks, and security policies
.
Write and optimize
complex SQL queries
for data analysis, transformation, and reporting.
Design and maintain
dimensional, ER, and Data Vault data models
for analytical and operational purposes.
Collaborate with business stakeholders and product owners to gather requirements, define technical solutions, and ensure timely delivery.
Work closely with
data scientists
and
analysts
to support
machine learning and data science initiatives
.
Implement
data management and data governance practices
, ensuring data quality, lineage, and compliance.
Use
GitLab
for version control, code review, and CI/CD pipeline management.
Develop automation scripts and workflows using
Python
for data ingestion, transformation, and quality checks.
Participate in
Agile development cycles
, contribute to sprint planning, and proactively resolve technical issues.
Actively collaborate with team members, maintain a positive and proactive attitude, and continuously learn new technologies and concepts.
Key Skills, Qualifications and Experience Needed [The candidate must demonstrate these in all stages of assessment]
Bachelor's or Master's degree in
Computer Science
,
Information Technology
,
Data Engineering
, or related field.
3-7 years
of professional experience in
data engineering or Snowflake development
.
SnowPro Core or Advanced Certification
(Data Engineer / Architect) is a plus.
Strong knowledge of Cloud Computing
concepts and experience with cloud data platforms.
Very good working knowledge
of data modeling techniques -- including
Dimensional
,
Entity-Relationship (ER)
, and
Data Vault
models.
Advanced SQL development
skills with experience in performance tuning and query optimization.
Hands-on experience with Snowflake architecture
, including
virtual warehouses, databases, schemas, and query optimization
.
In-depth understanding of
Snowflake internals
such as
roles, dynamic tables, streams, tasks, masking and row access policies, and resource monitoring
.
Experience working on
data-centric projects or data applications
across large datasets.
Proficiency in
GitLab
for code versioning, collaboration, and continuous integration.
Good working knowledge of
Python
for scripting and automation tasks.
Familiarity with
data science and machine learning
workflows, tools, and basic model deployment practices.
Understanding of
data management and data governance
principles -- including data quality, lineage, and metadata management.
Proven experience in
working with product owners and stakeholders
, translating business needs into technical deliverables.
Excellent
team collaboration, communication, and interpersonal skills
.
Self-initiator
, proactive learner, and adaptable to new technologies and evolving data ecosystems.
Working knowledge of
SQL Server
and/or
Oracle
databases.
Exposure to
investment banking
or
financial services
domain.
Understanding of
statistical concepts
and their application in data analysis.
Experience with
Power BI
or other BI/visualization tools.
Ability to
manage multiple projects
simultaneously in a fast-paced environment.
Other Key skills:
Good analytical and Problem-solving skills
Good communication skills
A thorough approach and Self starter
Focus on quality and delivery
Working together in teams.
Leadership and effective decision making.
Flexible Attitude
Excellent customer service
Job Types: Full-time, Permanent
Pay: 55,000.00-65,000.00 per year
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