Senior Data and AI Engineer

We are seeking an experienced Senior Data and AI Engineer to join our team. The Data and AI Engineer is responsible for designing, building, and maintaining robust data pipelines and AI systems that support the bank’s digital transformation, analytics, and automation initiatives. This role blends advanced data engineering with AI/ML expertise to deliver scalable, secure, and high-performing solutions that enable business insights, operational efficiency, and innovative customer experiences.  

The ideal candidate will have expertise in cloud based ETL tools such as Azure Data Factory (ADF), Apache Airflow, dbt, implementing medallion-style data architectures inside modern datawarehouse platforms such as BigQuery, Snowflake and Redshift, ML framework such as Pytorch, Tensorflow etc, Gen-AI platforms such as Google Vertex AI, Snowflake Cortex AI, AWS Bedrock etc, Experience with CI/CD pipelines, DevOps/MLOps practices, and version control (GitHub Actions or similar). 

Responsibilities: 

Design, implement, and maintain scalable data pipelines using ADF and dbt 

Develop and optimize ELT processes within a medallion architecture (Bronze, Silver, Gold, Semantics layers) 

Collaborate with data governor, analysts, and other stakeholders to understand data requirements and deliver high-quality datasets 

Implement data quality checks and monitoring throughout the data lifecycle 

Optimize query performance and data models for efficient analytics 

Contribute to data governance and documentation efforts 

Design and implement ML and AI models to enhance data insights and automation 

Integrate analytical models into existing data pipelines and workflows. 

Incorporate DevOps, MLOps, and AIOps principles for continuous delivery, monitoring, and automated maintenance of AI systems 

Monitor and optimize the performance of AI models and data pipelines, ensuring reliability and scalability 

Stay updated with the latest AI and machine learning technologies and best practices. 

Requirements: 

Bachelor's degree in Computer Science, Engineering, or related field 

5+ years of experience as a Data Engineer 

Strong proficiency in SQL and Python 

Hands-on experience with Azure Data Factory, AWS Glue or Apache Airflow for workflow orchestration 

Expertise in using dbt for data transformation and modeling 

Experience implementing medallion architecture or similar multi-layer data architectures 

Familiarity with cloud data platforms (e.g., BigQuery, Snowflake, or Redshift) 

Knowledge of data warehousing concepts and dimensional modeling 

Experience with developing ML and statistical models 

Strong problem-solving skills and attention to detail 

Excellent communication skills and ability to work in a collaborative environment 

Preferred Qualifications: 

Experience with Delta Lake or similar data lakehouse technologies 

Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch), NLP, and generative AI models 

Knowledge of data governance and compliance requirements 

Experience with CI/CD pipelines, DevOps/MLOps practices, and version control (GitHub Actions or similar) 

Experience dealing with data at financial institutions/banks 

Experience with FIS IBS core banking system 

Familiarity with Kafka, Kinesis or similar data streaming service 

Familiarity with microservices based and event driven architecture 

Experience with efficient code development and debugging using gen-ai tools like Github co-pilot