We
are seeking a detail-oriented and highly motivated Data Engineer to join our
growing Data & Analytics team.
In this role, you will be responsible for designing, building, and maintaining
robust data pipelines and infrastructure that power insights across the
organization. You’ll work closely with data scientists, analysts, and engineers
to ensure the integrity, accessibility, and scalability of our data systems.
Key
Responsibilities:
- Design, develop, and maintain scalable
data pipelines and ETL processes.
- Build and optimize data architecture to
ensure data quality and consistency.
- Integrate data from diverse internal
and external sources.
- Collaborate with cross-functional teams
to define data requirements and deliver solutions.
- Implement best practices for data
governance, security, and compliance.
- Monitor pipeline performance and
perform real-time troubleshooting of data issues.
- Participate in code reviews and
contribute to documentation and standards.
Required
Qualifications & Skills:
- Bachelor’s degree in computer science,
Engineering, or a related field (or equivalent practical experience).
- 5+ years of professional experience in
data engineering.
- Solid understanding of SQL and
proficiency in at least one programming language, such as Python, Java, or
Scala.
- Practical experience building and
maintaining data pipelines using tools like Apache Airflow or DBT.
- Hands-on experience with cloud
platforms (AWS, GCP, Azure) and data warehousing solutions (Redshift, BigQuery,
Snowflake).
- Familiarity with big data technologies
and frameworks, including Spark, Kafka, and Hadoop.
- Demonstrated ability to solve complex
problems with a strong focus on detail.
- Experience implementing CI/CD practices
for data workflows.
- Working knowledge of data modelling
principles and schema design.
- Exposure to machine learning pipelines
or real-time analytics systems is a plus
Skills Required
- Bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience
- 5+ years of professional experience in data engineering
- Solid understanding of SQL and proficiency in at least one programming language such as Python, Java, or Scala
- Experience building and maintaining data pipelines using tools such as Apache Airflow or dbt
- Hands-on experience with cloud platforms such as AWS, GCP, or Azure
- Experience with data warehousing solutions such as Redshift, BigQuery, or Snowflake
- Familiarity with big data technologies including Spark, Kafka, and Hadoop
- Ability to solve complex problems with strong attention to detail
- Experience implementing CI/CD practices for data workflows
- Working knowledge of data modeling principles and schema design
- Exposure to machine learning pipelines or real-time analytics systems
What We Do
Kavi Global is a data analytics and AI company that helps enterprises make intelligent, data-driven decisions. It provides analytics software, solutions, and services spanning strategy, design, development, implementation, and support. Its capabilities include business intelligence, data warehousing, big data, advanced analytics, machine learning, data management, and AI, serving organizations across multiple industries and supporting digital transformation initiatives.
