CHI Software

We are looking for an experienced Data Engineer to leverage their skillset in a fast-paced financial trading environment. You will be responsible for designing, developing, and maintaining data pipelines and infrastructure across GCP , and Oracle-based systems, ensuring high-performance data flows that support trading, risk, and compliance functions. This role requires a deep understanding of cloud architecture, large-scale data processing, and a strong grasp of agile delivery practices.
 

About the client
 

An international consulting firm that helps companies of all sizes have a better impact on the world. Company capabilities focus on supporting the private and public sectors with their people, processes, and digital technology challenges.
 

What You Will Do
 

● Design, build, and maintain scalable data pipelines primarily within Google Cloud Platform
 

● Develop integration and transformation workflows between cloud data services and on-prem Oracle databases
 

● Work closely with trading, risk, and analytics teams to understand data requirements and deliver real-time and batch data solutions
 

● Optimise and monitor performance of data systems to support latency-sensitive trading applications
 

● Collaborate with cross-functional teams using Agile/Scrum methodologies to deliver business-critical data projects
 

● Ensure robust data governance, lineage, and compliance (including MiFID II, FCA, and other regulatory standards)
 

● Automate data workflows using Terraform, CI/CD pipelines, and containerisation tools (Docker/Kubernetes)
 

What you will bring
 

● Strong experience with Google Cloud Platform (GCP) e.g. BigQuery, DataPlex, DBT, Pub/Sub, Dataflow, S3, Glue, Redshift
 

● Expertise in Oracle SQL, PL/SQL, and working with complex stored procedures and large datasets
 

● Proficiency in programming languages such as Python, Java, or Scala
 

● Experience with streaming and messaging systems (e.g. Jenkins, GitLab), and container orchestration (Kubernetes)
 

● Experience working with Infrastructure as Code, preferably Terraform, to manage cloud data infrastructure.
 

● Deep understanding of data modelling, data warehousing, and ETL/ELT design patterns
 

● Familiarity with Agile development practices (Scrum, Kanban, Jira)
 

● Exposure to financial markets, trading systems, or related high-performance environments is a strong plus
 

Nice to have
 

● GCP certification (e.g., Professional Data Engineer or similar) will be considered a strong advantage.
 

● Experience with Amazon Web Services (AWS)
 

● Knowledge of regulatory reporting, market data, or trade surveillance systems
 

● Experience with Apache Airflow, DBT, or similar orchestration tools
 

● Understanding of data security practices and compliance frameworks

The CHI Software team is not standing still. We love our job and give it one hundred percent of us! Every new project is a challenge that we face successfully. The only thing that can stop us is… Wait, it’s nothing! The number of projects is growing, and with them, our team too. And now we need a Data Engineer.
 

Project Description:

It is a real-time data processing and analytics solution for a high-traffic web application. 
Tech stack.
AWS: AWS Glue Studio, Redshift, RDS, Airflow, AWS Step Function, Lambda, AWS Kinesis, Athena, Apache Iceberg, AWS Data Brew, S3, OpenSearch, Python, SQL, CI/CD, dbt, Snowflake

 Responsibilities:

• Design a scalable and robust AWS cloud architecture;
• Utilize AWS Kinesis for real-time data streaming and aggregation;
• Implemente AWS Lambda for serverless data processing, reducing operational costs;
• Configured AWS RDS (Relational Database Service) for structured data storage and AWS DynamoDB for NoSQL requirements;
• Ensured data security and compliance with AWS IAM (Identity and Access Management) and encryption services;
• Developed and deployed data pipelines using AWS Glue for ETL processes;
• Wrote Python scripts and SQL queries for data transformation and loading;
• Set up continuous integration and continuous deployment (CI/CD) pipelines using AWS CodePipeline and CodeBuild;
• Monitored system performance and data quality using AWS CloudWatch and custom logging solutions;
• Collaborated with other teams to integrate data sources and optimize data flow;
• Achieve a highly scalable real-time data processing system, resulting in a 40% increase in data analysis efficiency and a significant reduction in operational costs.
• Build ETL pipelines from S3 to AWS OpenSearch by AWS Glue
• Upper-Intermediate or higher English level.

About the Role
 

Company domain - automotive industry.
We are looking for Data Engineers to join a managed service team delivering modern data products.
 

The role is focused on hands-on implementation under defined standards and senior guidance. You will contribute to building data products, ensuring quality and compliance with established frameworks.
 

Responsibilities
 

• Implement pipelines and data transformations
• Build analytical and source-aligned data products
• Follow established standards (data contracts, modeling patterns, testing strategies)
• Work in cross-functional domain teams
• Participate in pair-programming and knowledge transfer
• Support monitoring and operational excellence of delivered data products
   

Required Technical Stack
 

Mandatory experience with:
 

• AWS
• Azure
• Snowflake
• dbt
• Witboost
• Dreamio
• Modern ELT/ETL practices
• CI/CD in data environments
• Automated testing for data pipelines
   

Required Experience
 

• 1–3 years in Data Engineering
• Previous assignments delivering pipelines and data products
• Familiarity with Data Mesh
• Basic understanding of DataOps
• Understanding of governance, lineage, SLAs
• Comfortable working in Agile cross-functional teams