Data Engineer (SQL & ETL)

Overview

Permanent, full-time, hybrid (3 days per week in an office).

Connecting clients to markets – and talent to opportunity.

With 4,300 employees and over 400,000 retail and institutional clients from more than 80 offices spread across five continents, we’re a Fortune-100, Nasdaq-listed provider, connecting clients to the global markets – focusing on innovation, human connection, and providing world-class products and services to all types of investors.

Whether you want to forge a career connecting our retail clients to potential trading opportunities, or ingrain yourself in the world of institutional investing, The StoneX Group is made up of four segments that offer endless potential for progression and growth.

Business Segment Overview: Engage in a deep variety of business-critical activities that keep our company running efficiently. From strategic marketing and financial management to human resources and operational oversight, you’ll have the opportunity to optimize processes and implement game-changing policies.

Responsibilities

Position Purpose: We are seeking a skilled Data Engineer to design, develop, and implement scalable data solutions that support the organization’s regulatory, financial, operational, and analytical needs. This role is pivotal in modernizing our data infrastructure by transforming our on-premises SQL data warehouse into a next-generation Data Lakehouse using Databricks.

Technology Ecosystem:

• Databases: Microsoft SQL Server (T-SQL, SSIS, SSRS).
• Programming languages: Python, PySpark, Scala
• Cloud: Azure, AWS
• Big Data: Hadoop

Primary duties will include: 

Data Processing & Pipelines:

• Develop and optimize data pipelines using PySpark, Scala, and Python for data transformation, aggregation, and analysis.
• Build and maintain ETL processes across development, staging, and production environments, ensuring seamless operation of intraday data feeds and nightly jobs.

Data Warehouse Development:

• Collaborate with data warehouse leads to enhance multi-dimensional data warehouses by implementing new features and expanding functionality.
• Design data processing pipelines and logical/physical database schemas to support reporting and analytics.

Reporting & Troubleshooting:

• Create recurring/ad-hoc reports and automated data feeds, utilizing tools like SQL Server Reporting Services (SSRS).
• Troubleshoot data issues, validate results, and perform ad-hoc data analysis to address business needs.

Collaboration & Optimization:

• Work closely with development teams, senior management, and other departments to ensure alignment on database and reporting solutions.
• Optimize SQL queries, stored procedures, and data processing workflows to maximize performance.

Qualifications

To land this role you will need:

• 3-5 years of experience developing software in a professional environment (preferably financial services but not required).
• 5+ years of experience with Microsoft SQL Server (T-SQL, SSIS, SSRS).
• Proficiency in Spark, Databricks, and big data processing technologies (e.g., Hadoop).
• Expertise in building and managing ETL processes and data pipelines using Python, PySpark, and Scala.
• Practical knowledge of data warehouse concepts (Kimball methodology).
• Familiarity with .NET development, event-driven ETL, and SDLC frameworks.
• Experience creating data transformation and aggregation jobs in Scala/Spark.
• Ability to design scalable data processing pipelines and write unit tests for data transformations.
• Analytical and results-driven approach to solving business problems using technology.
• Hands-on experience working in an agile/SCRUM environment.
• Strong communication skills for both technical and non-technical stakeholders, including senior management and cross-functional teams.
• Fast learner with a passion for exploring and mastering new technologies.
• Detail-oriented team player with a proactive mindset.
• Comfortable working in a fast-paced, high-growth environment.

Education / Certification Requirements:

• Bachelor’s degree or relevant work experience in Computer Science, Mathematics, Data Engineering or related technical discipline.

Working environment:

• Hybrid (2 days from home, 3 days from the office) from Cracow office will at Mogilska 35 street.

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