Data Engineer

Job Summary

An exciting opportunity for Data Engineer to be a part of a project for strategic initiatives in architecting, designing and building next-generation cloud-based data platforms.

Mandatory Skill-set

• Degree in Data Engineering, Computer Science, Information Technology;
• At least 5 years of experience in data engineering and modelling;
• Strong hands-on exposure in data science, data analytics and / or data engineering;
• Deep understanding of system design, data structure and algorithms, data modelling, data access, and data storage;
• Advanced SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases;
• Good understanding in using cloud technologies such as AWS, Azure, and Google Cloud;
• Experience with orchestration frameworks such as Azure Data Factory, Airflow;
• Experience with distributed data technologies such as Spark, Hadoop;
• Proficiency in programming languages such as Python, R, Java, or Scala;
• Familiarity with building and using CI/CD pipelines;
• Familiarity with DevOps tools such as Git, Terraform, Git;
• Strong hands-on exposure with ETL Extract, Transform, Load tools;
• Possess strong written and verbal communication abilities, effectively conveying information to various stakeholders.

Desired Skill-set

• Experience in designing, building, and maintaining batch and real-time data pipelines;
• Experience with Databricks or Snowflake.

Responsibilities

• Work closely with the various team in architecting, designing and building ingestion pipelines to collect, clean, merge, and harmonize data from different source systems;
• Involved in architecting and scaling data analytics infrastructure on cloud environment; development of systems, architectures, and platforms that can scale large volume and variety;
• Architect and build ingestion pipelines to collect, clean, merge, and harmonize data from different source systems;
• Improve and optimize the workloads, processes to ensure that performance levels can support continuous accurate, reliable, and timely delivery of data products;ensure maximum database uptime;
• Monitoring of databases and ETL systems for database capacity planning and maintenance, monitoring, and performance tuning; diagnose issues and deploy measures to prevent recurrence;
• Construct, test, and update useful and reusable data models based on business data needs;
• Engagement and collaboration with product managers, software engineers, data analysts and data scientists to build scalable and data-driven platforms and tools;
• Collaborate with data stewards to establish and enforce data governance policies, best practices and procedures;
• Assist to maintain master data catalogue to document data assets, metadata and lineage;
• Implement and enforce data security best practices, including access control, encryption, and data masking, to safeguard sensitive data;
• Involved in managing production services that provide analytics capabilities to our various data users across the division.

Should you be interested in this career opportunity, please send in your updated resume to [Confidential Information] at the earliest.

When you apply, you voluntarily consent to the disclosure, collection and use of your personal data for employment/recruitment and related purposes in accordance with the SCIENTE Group Privacy Policy, a copy of which is published at SCIENTE's website (https://www.sciente.com/privacy-policy).

Confidentiality is assured, and only shortlisted candidates will be notified for interviews.

EA Licence No. 07C5639