Data Engineer (SQL, Python, PLSQL) at Tezza Business Solutions Limited June, 2024

Job Description 

  • We are seeking a talented and experienced Data Engineer to join our team.
  • The Data Engineer will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support our data analytics and business intelligence needs.
  • The ideal candidate will have a strong background in data engineering, a deep understanding of data architecture, and experience with big data technologies.

Key Responsibilities

  • Data Pipeline Development: Design, develop, and maintain scalable data pipelines to process and analyze large datasets from various sources.
  • Data Integration: Integrate data from multiple data sources and ensure data quality, consistency, and reliability.
  • Data Warehousing: Build and maintain data warehouses and data lakes to support analytics and reporting needs.
  • Data Transformation: Implement data transformation and cleaning processes to ensure data is ready for analysis.
  • Performance Optimization: Optimize data processing performance and troubleshoot any issues related to data pipelines and infrastructure.
  • Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand their data needs and provide the necessary data infrastructure.
  • Documentation: Document data engineering processes, data flows, and infrastructure designs.
  • Security and Compliance: Ensure data security, privacy, and compliance with relevant regulations and standards.
  • Continuous Improvement: Stay up-to-date with the latest industry trends and technologies, and continuously improve data engineering practices and processes.


  • Education: Bachelor’s Degree in Computer Science / Information Technology, or a related field. Master’s degree is a plus.
  • Experience: Minimum of 3 – 5 years of experience in data engineering or a similar role.
  • Technical Skills: Proficiency in programming languages such as Python, Java, or Scala. Strong SQL skills.
  • Big Data Technologies: Experience with big data technologies such as Hadoop, Spark, Kafka, and NoSQL databases.
  • Data Warehousing: Experience with data warehousing solutions such as Amazon Redshift, Google BigQuery, or Snowflake.
  • ETL Tools: Familiarity with ETL tools and processes.
  • Cloud Platforms: Experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Analytical Skills: Strong analytical and problem-solving skills.
  • Communication Skills: Excellent verbal and written communication skills.
  • Collaboration: Ability to work effectively in a collaborative team environment.
  • Certification: Relevant certifications (e.g., AWS Certified Data Analytics, Google Professional Data Engineer) are a plus.

Application Closing Date
Not Specified.

How to Apply
Interested and qualified candidates should:
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