Reporting to the Director of Data Platform and Engineering, the Data Engineering Senior Manager plays a key role in executing the firm’s data strategy by overseeing the architecture, implementation, and optimization of scalable data platforms. This role supports the delivery of high-quality, secure, and high-performing data solutions that enable data-driven decision-making across the firm. The Senior Manager collaborates closely with cross-functional teams to drive operational efficiency and maximize customer value, while also ensuring adherence to data privacy and governance standards.
Duties and Responsibilities
- Support the execution of the firm’s data strategy by contributing to initiatives that uphold high standards of data quality, security, and performance in alignment with organizational objectives.
- Manage the implementation and enhancement of scalable data architectures that support analytics, machine learning, and AI capabilities under the guidance of the Director
- Lead the development and continuous evolution of scalable, robust, and business-aligned data platforms & pipelines, driving the adoption of modern tools and technologies, including cloud-native services, distributed computing, and real-time data processing.
- Collaborate with cross-functional partners—including AI, BI, Product, Operations, and support teams—to align on project-level priorities and ensure integrated execution across teams.
- Design and implement robust processes and tooling to ensure comprehensive data visibility, enable actionable insights, and drive data-centric awareness across the organization.
- Contribute to the maintenance and improvement of data governance practices, helping to ensure data integrity, accessibility, and compliance with regulations such as GDPR.
- Translate technical concepts and progress updates into clear communications for internal stakeholders, supporting alignment with broader data and technology goal
- Assist in vendor assessments and contribute to the evaluation of third-party tools and services to ensure alignment with technical and budgetary goals.
- Hires, develops, coaches, and supervises direct reports. Conducts annual performance reviews.
Target Salary Range
$180,000 – $200,000 if located in Illinois
Qualifications
Education and/or Experience:
Required:
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field
- A minimum of 7 years of experience in data engineering
- A minimum of 3 years in a leadership
- Advanced knowledge of big data architecture, including tools such as Spark, Kafka, and architectures like Data Lake or Lakehouse
- Advanced knowledge of SQL, ETL tooling, and data modeling
- Skilled at crafting compelling data narratives through tables, reports, dashboards, and other visualization tools
- Demonstrated leadership abilities in building, mentoring, and scaling high-performing, cross-functional data engineering teams in a dynamic environment
- Proven experience in building and scaling data platforms in a cloud environment such as AWS, Azure, or GCP, with a focus on scalability, security, and performance
Preferred:
- Master’s degree in Computer Science, Engineering, or MBA
- Experience implementing and operating Databricks at scale
- Working knowledge of CI/CD pipelines for App and Infrastructure code
- Experience working in an Agile delivery model
Other Skills and Abilities:
The following will also be required of the successful candidate:
- Strong organizational skills
- Strong attention to detail
- Good judgment
- Strong interpersonal communication skills
- Strong analytical and problem-solving skills
- Able to work harmoniously and effectively with others
- Able to preserve confidentiality and exercise discretion
- Able to work under pressure
- Able to manage multiple projects with competing deadlines and priorities
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