Posted on: 20/05/2026
Description :
Role & Responsibilities :
- Build, develop, and maintain efficient and high-performance data pipelines across both cloud and on premises environments.
- Ensure the accuracy, adequacy, and legitimacy of data.
- Prepare ETL pipelines to extract data from various sources and store it in a centralized location.
- Analyse, interpret, and present results through effective visualization and reports.
- Identify critical metrics.
- Implement and instil best practices for effective data management.
- Monitor the use of data systems and ensure the correctness, completeness, and availability of data services.
- Optimize data infrastructure and processes for cost efficiency on AWS cloud and on premises
environments.
- Utilize Apache Airflow, NiFi, or equivalent tools to build and manage data workflows and integrations.
- Implement best practices for data governance, security, and compliance.
- Monitor and troubleshoot data pipeline issues to ensure timely resolution.
- Stay current with industry trends and emerging technologies in data engineering and cloud computing.
Preferred candidate profile :
- Proven experience as a Data Engineering Lead or in a similar role.
- Extensive hands-on experience with ETL and ELT processes.
- Strong expertise in data integrity and quality assurance.
- Proficiency in optimizing AWS cloud services and on-premises infrastructure for cost and performance.
- Hands-on experience with Apache Airflow and NiFi.
- Strong programming skills in languages such as Python, Java, or Scala.
- Experience with SQL and NoSQL databases.
- Experience in building and maintaining a single source of truth.
- Familiarity with data warehousing solutions like Amazon Redshift, Snowflake, or BigQuery.
- Strong problem-solving skills and the ability to work under pressure.
- Hands-on experience with data visualization tools such as Tableau, Power BI, or Looker.
- Experience in financial services is a must.
Educational Qualifications :
- Bachelors degree in Computer Science, Information Technology, Data Science, or a related field.
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Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1637505