to conduct interactive and practical training sessions for learners and professionals. The ideal candidate should have hands-on experience in data engineering tools, cloud platforms, and coding best practices, along with the ability to simplify complex concepts for diverse audiences.
Key Responsibilities:
Deliver engaging sessions on
Data Engineering fundamentals and advanced topics
.
Teach practical implementation of:
Data pipelines, ETL processes, and data warehousing.
SQL and NoSQL databases.
Python for Data Engineering.
Big Data tools
such as Hadoop, Spark, Kafka, Airflow.
Cloud platforms
- AWS, Azure, or GCP data services.
Guide learners on
code optimization, performance tuning, and best practices
.
Conduct
code reviews (PRs)
and teach students to optimize existing codebases.
Explain
CI/CD practices
and
data version control
.
Design
assignments, projects, and assessments
to evaluate learning outcomes.
Support learners during
doubt-solving sessions and project reviews.
Stay updated with
industry trends
and incorporate them into the curriculum.
Required Skills & Expertise:
Strong proficiency in
Python, SQL
, and
data pipeline design
.
Good understanding of
data warehousing
(Snowflake, Redshift, BigQuery, etc.).
Experience with
ETL tools
(Informatica, Talend, Apache NiFi, etc.).
Familiarity with
cloud data services
(AWS Glue, Azure Data Factory, GCP Dataflow).
Basic knowledge of
machine learning pipelines
is a plus.
Hands-on experience with
GitHub
,
version control
, and
code collaboration
.
Excellent communication and presentation skills.
Prior experience as a
trainer, mentor, or corporate instructor
is desirable.
Preferred Qualifications:
Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
Industry experience in data engineering projects (3-5 years).
Certification in AWS / Azure / GCP data engineering (preferred).
Job Type: Contractual / Temporary
Contract length: 6 months
Pay: From ?650,000.00 per month
Work Location: In person
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