Drive the design, development, and optimization of ETL/ELT pipelines

Design, deploy and maintain scalable and efficient data foundation

Ensure high data quality and availability for analytics and reporting

Ensure appropriate storage of data in line with relevant legislation and organizational policies

Build-in security, compliance, scalability, efficiency, reliability, fidelity, flexibility, and portability into data solutions

Collaborate with stakeholders to meet data requirements and deliver solutions

Provide mentorship to junior data engineers

Minimum 3 years of experience in data engineering or similar role

Certification in relevant technologies (e.g., AWS Certified Data Analytics, Snowflake SnowPro Core Certification)

Background in machine learning and data mining techniques

Proficiency with data governance and data management best practices to ensure data quality and compliance

Understanding of Agile development methodologies

Competency in domains such as Finance, Consumer, Commercial, P&C, Supply Chain, Product, and Life Sciences

Expertise in data from Salesforce, DCE (Digital Consumer Engagement), ERP, and Finance Systems

Showcase of Snowflake skills: Data warehousing, data integration, and data transformation

Proficiency with Amazon AWS tools: S3, Redshift, Glue, Lambda, EMR, and other AWS data services

Familiarity with open-source technologies like Apache Kafka, Apache Spark, and other relevant tools

Deep expertise in SQL and NoSQL databases

Flexibility to use data visualization tools to monitor pipeline performance

Strong understanding of data security and compliance standards

Excellent problem-solving and analytical capabilities

Strong communication and collaboration skills, with English proficiency at a B2 level or higher

Data build tool (dbt) skills: Data transformation and modeling

Matillion: ETL processes and data transformation