This is a key role for Bernstein that involves working with high-volume trading data to improve the accuracy, timeliness, and completeness of the firm’s regulatory reporting and trade recordkeeping. We are looking for a data expert who is passionate about technology and eager to learn more about financial services and our Equity broker dealer business.

The Data Engineer will be responsible for receiving and transforming high-volume Equity trading data for onward reporting to the firm’s regulators and business users. Trading data is ingested to Microsoft Azure Synapse, transformed using Apache Spark, and written to Delta Lake tables on Azure. The successful candidate will help to migrate legacy SQL Server tables and T-SQL stored procedures to our future-state Microsoft Azure data platform.

The Data Engineer will propose and implement improvements to the firm’s regulatory reporting implementation and will work with regulatory control and compliance to understand reporting requirements and deliver enhancements. The Data Engineer’s goal is to ensure that accurate, timely and complete data is supplied to regulators and business users in a format that they can use and understand.

The Data Engineer will work closely with Equity trading and trade support to understand trading scenarios and validate that Consolidated Audit Trail (CAT) Reporting accurately reflects the firm’s Equity trading activity. The successful candidate will promote innovative data analysis techniques and will gain knowledge in cash & electronic trading scenarios, trading technology, data analysis, design, and regulatory compliance.

The key job responsibilities include, but are not limited to:

Enhance and maintain the Microsoft Azure Synapse and Spark data pipelines that generate Bernstein’s CAT reporting and populate Bernstein’s trading records.
Migrate legacy SQL Server tables and T-SQL stored procedures to Microsoft Azure Synapse, PySpark, and Delta Lake
Understand Equity trading scenarios and how these are represented in the data models of Bernstein trading systems.
Understand how CAT Reporting applies to Bernstein’s Equity trading business
Identify and troubleshoot data issues by analyzing high-volume datasets in innovative ways, e.g. by using data analytics tools such as Python, Azure Synapse, and PowerBI
Design and implement transactional and reference data reconciliations to maintain data quality.
Support critical regulatory reporting processes in production
Work closely with business users to create dashboards and reports that improve risk management and enable better business decisions
Hybrid role with a minimum of 3 days in the office

The role provides in-depth learning on how to work with high-volume financial services data and would offer a motivated technologist the opportunity to champion the use of new technology within a large financial services organization. The Data Engineer will be trained in Equity trading scenarios and CAT Reporting, areas that are in high demand within the financial services industry.

The role provides the following opportunities for learning and professional growth:

Gain in-depth financial services knowledge, including Equity trading scenarios
Learn the data model and business processes of a major brokerage firm
Gain experience in PySpark data analysis and Azure cloud-based technologies such as Azure Synapse, Spark, Delta Lake, and PowerBI
Become an expert in CAT Reporting

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