The Data Engineer will be responsible for designing, implementing, and optimising data pipelines and data solutions using AWS and Snowflake. The successful candidate will work closely with Data Analysts, Data Scientists, and other stakeholders to ensure efficient data storage, processing, and accessibility in a cloud environment.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines using AWS services (e.g., S3, Glue, Lambda, Redshift) and Snowflake.
• Implement best practices for data storage, transformation, and optimisation in a cloud environment.
• Develop data models to support business intelligence and analytics needs.
• Ensure data integrity, consistency, and reliability through data validation and quality assurance processes.
• Optimise data performance and cost efficiency in Snowflake and AWS.
• Collaborate with cross-functional teams to define data architecture and infrastructure requirements.
• Automate data workflows and monitor performance for continuous improvements.
• Troubleshoot and resolve data-related issues.

Requirements:

• Bachelor’s degree in Computer Science, Information Systems, or a related field.
• 5+ years of experience in Data Engineering.
• Strong proficiency in AWS cloud services, particularly S3, Glue, Lambda, Redshift, and IAM.
• Hands-on experience with Snowflake, including data warehousing concepts, performance tuning, and optimisation.
• Expertise in SQL for data modelling, transformation, and querying.
• Experience with ETL/ELT processes and tools.
• Understanding of data governance, security, and compliance in a cloud environment.
• Proficiency in Python or another scripting language for automation.

• Preferred Skills & Experience:

• Experience with data orchestration tools like Apache Airflow.
• Knowledge of DevOps practices and CI/CD pipelines for data workflows.
• Familiarity with Big Data technologies such as Spark or Kafka.
• Exposure to machine learning workflows and MLOps.
• Experience in financial, banking, or insurance sectors.

Key Competencies:

• Strong analytical and problem-solving skills.
• Excellent communication and interpersonal skills.
• Ability to work independently and collaboratively within a team.
• Detail-oriented with a strong focus on data quality and integrity.
• Ability to adapt to a fast-paced and evolving technology landscape.

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