Position : Data Engineer
Data Engineer is an individual who will build the data architecture framework for modern data platforms, following the information governance policies, standards and principles, including modeling, metadata, security, reference data providing options with respect to end state data architecture and implementation of processes, awareness of DG technologies.

Responsibilities

• Administering and testing the reliability of the data systems; monitoring the performance and stability of the systems as the requirements change.
• Configuring and validating the data sources; developing and improvising the integration and analytical tools for efficient data procurement and analysis, including the use of Artificial Intelligence (AI), by developing and piloting AI models and prototype applications; validating whether business problems are addressed.
• Developing and managing the architecture of the data platform and data modelling by evaluating the business needs and objectives.
• Utilizing niche tools to view and visualize the generated data to support business intelligence and data-driven solutions; maintaining compliance with SLAs, data governance, and security policies.
• Ability to extract, transform and consume data using the best- in-class tools and techniques; selecting and applying appropriate AI technologies and tools to solve problems.
• Implementing information governance standards, policies and processes/procedures as required while developing modern data platforms
• As part of the AI & Data Analytics team, performing data visualizations (i.e., using tools to create dashboards based on requirements).

Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field.
• 3-5 years of experience in data engineering, data pipelines, and ETL processes. Financial services experience
  preferred.
• Expertise in SQL, Python, ETL frameworks, big data tools like Hadoop or Spark, experience in cloud platforms (AWS, GCP, Azure).
• Strong experience in designing and maintaining data architecture and pipelines. Familiar with data warehousing, ETL processes, and data governance.