Data Engineer - Inteliment

3-5 years of relevant experience in a data engineering role.

As a Data Engineer, you will contribute to cutting-edge global projects and innovative product initiatives, delivering impactful solutions for our Fortune clients. In this role, you will take ownership of the entire data pipeline and infrastructure development lifecycle from ideation and design to implementation and ongoing optimization. Your efforts will ensure the delivery of high-performance, scalable, and reliable data solutions. Join us to become a driving force in shaping the future of data infrastructure and innovation, paving the way for transformative advancements in the data ecosystem.

• Data Pipeline Development:

  Build, maintain, and optimize ETL/ELT pipelines for seamless data flow.

• Data Integration:

  Consolidate data from various sources into unified systems.

• Database Management:

  Design and optimize scalable data storage solutions.

• Data Quality Assurance:

  Ensure data accuracy, consistency, and completeness.

• Collaboration:

  Work with analysts, scientists, and stakeholders to meet data needs.

• Performance Optimization:

  Enhance pipeline efficiency and database performance.

• Data Security:

  Implement and maintain robust data security and governance policies.

• Innovation:

  Adopt new tools and design scalable solutions for future growth.

• Monitoring:

  Continuously monitor and maintain data systems for reliability.
• Data Engineers ensure reliable, high-quality data infrastructure for analytics and decision-making.

• Bachelor s or Master s degree in Computer Science, Information Technology, or a related field.
• Certifications in the related field will be an added advantage.

• Must have experience with SQL, Python, and Hadoop.
• Good to have experience with Cloud Computing Platforms (AWS, Azure, GCP, etc.), DevOps practices, and Agile methodologies.
• Experience with ETL or similar technologies will be an advantage.

• Core Skills:

  Proficiency in SQL, Python, or Scala for data processing and manipulation.

• Data Platforms:

  Experience with cloud platforms such as AWS, Azure, or Google Cloud.

• Tools:

  Familiarity with Apache Spark, Kafka, and modern data warehouses (e.g., Snowflake, BigQuery, Redshift).

• Soft Skills:

  Strong problem-solving abilities, collaboration, and communication skills.

• Additional:

  Knowledge of SAP would be an advantage.