Job summary
Job post source
This job is from a recruiting firm hiring for a separate company as indicated by the phrase 'I'm advising a Hedge Fund' rather than direct company language.
Job overview
The Senior Data Engineer role at a hedge fund involves building and maintaining cloud-native data infrastructure to support quantitative research, trading, and enterprise data needs, impacting the firm's data capabilities and performance.
Responsibilities and impact
The candidate will design and manage scalable data pipelines using AWS services, develop ETL/ELT processes, support data ingestion and transformation for modeling and analytics, ensure data quality and governance, automate infrastructure workflows, mentor junior engineers, and collaborate with cross-functional teams to maintain secure and efficient data operations.
Experience and skills
The role requires 5+ years in data engineering preferably in finance-related firms, deep expertise in AWS data stack, strong Python and SQL skills, knowledge of data modeling and warehousing, experience with orchestration and streaming technologies, and familiarity with financial market data; AWS certifications and containerization experience are preferred.
Job location and travel
The position is located in New York City with a hybrid work model.
Company overview
Goldman Lloyds is a specialist search firm headquartered in New York, serving some of the world's leading trading firms, including buy-side and investment banking clients. The company generates revenue by providing recruitment and talent acquisition services, particularly focusing on high-frequency trading (HFT) and quantitative fund environments. Known for its expertise in the financial sector, Goldman Lloyds offers roles such as Quantitative Developers and Network Architects, emphasizing its strong presence in the competitive finance job market.
How to land this job
Position your resume to highlight your extensive experience with AWS data stack tools like S3, Glue, Lambda, Redshift, and Athena, emphasizing your ability to build scalable, cloud-native data pipelines tailored for quantitative research and trading environments.
Focus on showcasing your skills in Python, SQL, and ETL/ELT optimization, along with any experience you have in streaming technologies such as Kinesis or Kafka, which are critical for real-time data processing in this role.
Apply through multiple channels including Goldman Lloyds' official corporate careers page and LinkedIn to increase your chances of visibility and consideration for the Senior Data Engineer role.
Connect with data engineering and technology team members at Goldman Lloyds on LinkedIn to learn more about the team culture and expectations; start conversations by referencing recent projects or technologies mentioned in the job description, or ask about their experience working on data infrastructure for hedge fund strategies.
Optimize your resume for ATS by incorporating relevant keywords from the job description such as 'AWS data stack,' 'ETL/ELT processes,' 'Python,' 'data governance,' and 'cloud-native infrastructure' to ensure it passes automated screening effectively.
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