About the role

Design and optimize scalable data ingestion pipelines and transformations for an AWS-based Lakehouse platform in a banking environment. Transition data processing from interval-based batch ingestion to near-real-time streaming using tools like Debezium and Flink.

What they look for

SQL Python Debezium MSK Flink AWS Lake Formation Redshift CDC ETL/ELT Lakehouse Architecture AWS Glue S3 Athena Data Pipeline Development Data Quality Validation Streaming Data Processing

Requirements

Requires a Bachelor's degree and 4+ years of experience in data engineering with strong proficiency in SQL, Python, and AWS data services. Experience with CDC, streaming technologies, and the banking domain is highly valued.

Full description

About GFT

GFT Technologies is an AI-centric global digital transformation company. We design advanced data and AI transformation solutions, modernize technology architectures and develop next-generation core systems for industry leaders in Banking, Insurance, Manufacturing and Robotics. Partnering closely with our clients, we push boundaries to unlock their full potential. With deep industry expertise, cutting-edge technology, and a strong partner ecosystem, GFT delivers responsible AI-centric solutions that combine engineering excellence, high-performance delivery, and cost efficiency. Our team of 12,000+ technology experts operates in 20+ countries worldwide offering career opportunities at the forefront of software innovation.

Role Summary

We are looking for a Data Engineer to design, build, and optimize ingestion pipelines and data transformations for an AWS-based Lakehouse platform in a banking environment.

This role focuses on implementing scalable data pipelines using Debezium, MSK, Flink, Python, AWS Lake Formation, and Redshift. The Data Engineer will support the transition from interval-based ingestion to near-real-time data processing, working under the technical direction of the Senior Data Engineer / Data Platform Lead.

Key Responsibilities

Build and execute data ingestion pipelines using Debezium, MSK, Flink, and Python.

Support the transition from hourly batch ingestion to near-real-time ingestion within minutes.

Implement CDC, streaming, and batch data processing patterns.

Develop bronze, silver, and gold data transformations within the Lake Formation-based Lakehouse.

Configure and optimize Redshift tables, schemas, and data loading processes.

Work with the Senior Data Engineer / Data Platform Lead to ensure pipelines align with platform architecture and design standards.

Perform data quality checks, validation, reconciliation, and issue investigation.

Optimize pipeline performance, reliability, scalability, and cost efficiency.

Collaborate with data architects, engineers, business teams, and banking stakeholders to support reporting and analytics needs.

Required Skills

Strong SQL and Python skills.

Hands-on experience building scalable data pipelines.

Experience with data ingestion, ETL/ELT, data transformation, and data processing.

Experience with CDC, streaming technologies, and near-real-time data pipelines.

Practical knowledge of AWS data services, Lakehouse architecture, and cloud-based data platforms.

Experience with Debezium, Kafka/MSK, Flink, AWS Lake Formation, Glue, S3, Athena, or Redshift.

Strong understanding of data quality validation, reconciliation, and performance optimization.

Ability to work effectively within a technical engineering team and follow architecture guidance.

Domain Experience

Banking domain experience is a plus.

Experience with banking data, transaction data, customer/account data, regulatory reporting, financial reporting, AML/KYC, or risk data is highly valuable.

Nice to Have

Experience with Apache Airflow or other orchestration tools.

Experience with data catalog, lineage, metadata, and governance practices.

Exposure to Databricks, Snowflake, BigQuery, Synapse, or similar modern data platforms.

Experience working in Agile delivery teams using Jira and Confluence.

Key Qualifications

Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Data Analytics, or a related field.

4+ years of experience in Data Engineering, Data Pipeline Development, ETL/ELT, or similar roles.

Proven experience building data pipelines in cloud or Lakehouse environments.

Experience in banking, financial services, or regulated industries is an advantage.

(Note: Due to the high volume of applications we receive, we are unable to respond to every candidate individually. If you have not received a response from GFT regarding your application within 10 workdays, please consider that we have decided to proceed with other candidates. We truly appreciate your interest in GFT and thank you for your understanding)