Develop our comprehensive data processing pipeline transforming on-premises Kafka streams into both actionable business insights and regulatory compliance reports through AWS cloud services (S3, Glue, Athena, EMR).

Design robust ETL processes and build automated, scalable data solutions aligned with our zero-maintenance vision, delivering high-quality outputs for both business decision-making and regulatory requirements. About your team:

We are the Realtime Order Analytics and Reporting team, a dynamic group focused on transforming financial transaction data into valuable business intelligence and regulatory reporting.

Our team:

Works with cutting-edge technologies, including AWS cloud services and realtime data processing

Operates in a collaborative environment where innovation and ideas are encouraged

Maintains a balance between technical excellence and business impact

Values automation and efficiency in all our solutions

Fosters continuous learning and professional development

Plays a critical role in supporting business decision-making and ensuring regulatory compliance

Embraces agile methodologies to deliver high-quality solutions efficiently

We're looking for someone who shares our passion for data engineering and wants to make a significant impact by turning complex financial data into actionable insights.

What will be your responsibilities:

Designing, developing, and maintaining ETL workflows using AWS services

Processing data from Kafka streams and S3 storage to generate insights

Implementing data transformation logic using Python, PySpark, and PyAthena

Creating and optimizing data models for both analytical and regulatory reporting needs

Building automated data quality checks and monitoring systems

Developing and maintaining documentation for data pipelines and processes

Troubleshooting and resolving data pipeline issues

Contributing to architectural decisions for data infrastructure

Ensuring data solutions meet performance, security, and compliance requirements

Continuously improving our data systems for scalability and reduced maintenance

3+ years of professional software engineering experience in Python, PySpark and PyAthena

3+ years of professional experience in Python as a primary language (non-scripting)

Extensive experience in Pandas or NumPy

Experience with ETL processes and data warehousing concepts

Familiarity with cloud technologies, particularly AWS (S3, Glue, Athena, EMR)

Experience using ELK Stack (Elasticsearch, Logstash, Kibana)

Thorough understanding of databases and SQL

1+ years of professional experience with Linux operating systems

An analytical mind and business acumen

Strong communication skills

Good to have:

Experience with financial markets or the brokerage industry

Experience with business intelligence tools, especially Tableau

Experience with version control systems (e.g., Git, BitBucket)

Experience with CI/CD Practices and Tools

To be successful in this position, you will have the following:

Self-motivated and able to handle tasks with minimal supervision.

Superb analytical and problem-solving skills.

Excellent collaboration and communication (Verbal and written) skills.

Outstanding organizational and time management skills.

RELOCATION ASSISTANCE AND VISA SPONSORSHIP ARE AVAILABLE!