Data Engineering Manager

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Job description

DATA ENGINEERING MANAGER AT BOUTIQUE ANALYTICS FOCUSED HEDGE FUND

Base Salary is $225K to $250K (based upon candidate and experience); Plus Bonus; and Excellent Benefits

Incredible Organization with Equally Incredible People Houston, TX Onsite Four (4) Days per Week

Multi-office, solidly established, international, boutique analytics-focused hedge fund is looking for an experienced software and engineering professional to join its growing team in Houston, TX as a Data Engineering Manager. In this role, you will shape the strategy for the firm's data platform and help build the software and systems needed to deliver enhanced capabilities. The Data Engineering Team is responsible for building and maintaining our storage infrastructure and ETL processes. This team also serves as the owner for the data collected by all lines of business and supports the interface layer that delivers data for users and applications across the front, middle, and back office.

The Data Engineering Manager will oversee the team and collaborate with others to ensure that standardized technologies are adopted across the firm. The position provides the opportunity to build out the foundational functionalities of our enterprise platform, which provides components utilized by applications throughout Roscommon, including web deployment and workflow orchestration. This is a hands-on role, and candidates should have experience supporting production code in cloud environments. A successful candidate in this position will drive the evolution of the firm's technological capabilities, improve aspects of the development lifecycle, and maintain high engineering standards.

REQUIREMENTS AND SKILLS

Strong Background in Software and Data Engineering, Ten Plus (10+) years.

Very Strong Python knowledge including object-oriented programming (OOP).

Broad knowledge and experience with relational databases (i.e., stored procedures, indexing, partitioning, table design, query optimization).

Expertise with all aspects of SQL.

Experience with designing and implementing data pipelines for quality, ingestion, validation, and related infrastructure.

Exposure to data warehouses (i.e., snowflake, redshift, big query).

Working knowledge of cloud environments (preferably AWS, ideally exposure to both windows and Linux), including networking.

Experience with automation/orchestration platforms (Airflow).

Extensive experience with version/source control systems (Git).

Exposure to commodities and weather-related data including electricity, congestion, natural gas, oil, and emissions (ISOs, data vendors, governments).

Experience working with large datasets.

Ability to execute independently, on a deadline, and under pressure.

Communication skills and project management experience.

Excellent troubleshooting and analytical skills.

Experience with data visualization and web user interfaces.

Familiarity with infrastructure as code (Terraform).

Exceptional attention to detail.

Ability to understand unfamiliar code bases (multi and mono repo structure) and debug applications.

Experience managing a team of developers.

Experience designing and architecting libraries.

Consistent track record managing and balancing priorities across a diverse set of stakeholders and guiding them toward strategic solutions.

Some knowledge of derivative pricing, products, and markets.

RESPONSIBILITIES AND DUTIES

Deliver the next iteration of our internal data platform.

Architect, develop, and maintain platform components.

Build infrastructure to make data sets accessible and useful.

Develop tools and processes for automated acquisition, validation, and organization of large volumes of structured and unstructured data from many sources.

Develop systems to improve and test data quality.

Support and educate team members on best practices in data engineering.

Serve as the lead code reviewer for the team.

Establish a strong engineering culture and high code quality standards.

Produce documentation for technical and non-technical audiences.

Provide leadership for the team by providing feedback on performance.

Manage data systems efficiently at scale through standardization, automation, testing, and monitoring.

Enforce standards for all phases of software development including source control and testing.

Work with business owners to regularly re-prioritize projects, while delivering both tactical and long-term objectives.

Develop well defined processes for integrating new technologies to meet both business and technical needs.

Drive the elimination of operational tasks through automation and self-service.

Drive efficient utilization of resources through metrics and reporting.

Architect, develop and maintain solutions for business teams and help them do the same.

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