Job Description

As a Senior Data Engineer, you will be playing a key role in shaping data strategies, utilizing extensive experience in languages like SQL, Python, and Java. You will be handling diverse databases, implementing big data technologies, managing ETL processes, and contributing to the evolution of data warehousing concepts on cloud platforms such as AWS, Azure, or Google Cloud.

Responsibilities:

•   Develop and implement a comprehensive data quality framework, including standards, processes, and procedures.​
  
  
• Conduct thorough data profiling to identify anomalies, inconsistencies, and inaccuracies in datasets. Experience in Telco, Fintech is a must.
  
  
•  Design and execute data cleansing processes to rectify data quality issues and improve overall data accuracy.​
  
  
• Implement robust monitoring mechanisms to continuously assess and report on data quality metrics.​
  Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders, to understand data requirements and quality expectations.​
•   Define and track key data quality metrics, providing regular reports and insights to relevant stakeholders.​
  
  
• Investigate and resolve data quality issues, performing root cause analysis to address underlying problems.​
  
  
• Maintain comprehensive documentation of data quality processes, standards, and remediation strategies.​
  
  
•    Develop and implement automated data quality checks and validation processes.​
       Conduct training sessions to educate team members on data quality best practices and standards.
  

Qualification

• Bachelor's or higher degree in Computer Science, Information Technology, or a related field. 
  
  
•  Minimum of 6 years of hands-on experience in data engineering roles. 
  
  
•  Proficient in languages such as SQL, Python, and/or Java. 
  
  
• Expertise in database systems such as PostgreSQL, MySQL, and/or NoSQL databases. 
  
  
•   Experience with big data technologies like Hadoop, Spark, or similar frameworks. 
  
  
•  Hands-on experience with ETL tools such as Apache Airflow, NiFi, Talend, or Informatica. 
  
  
•  Familiarity with cloud platforms, especially AWS, Azure, or Google Cloud. 
  
  
• Strong understanding of data warehousing concepts and experience with platforms mainly PostgreSQL Citus and other like Snowflake, Redshift, or BigQuery. 
  
  
• Proficient in using version control systems like Git for code and configuration management. 
  
  
• Strong analytical and problem-solving skills with an ability to think critically and adapt to evolving data challenges.