Data Architect, Corporate Services

Qualifications

• Education & Certifications • Bachelor’s degree, required • Concentration in computer science, engineering, information systems, or a related quantitative field, preferred • Master’s degree, preferred
• Professional Experience • 10+ years of overall relevant data engineering or data architecture experience, required • 7+ years in financial services such as private equity, asset management, investment banking, hedge fund, or fund administration, preferred • Demonstrated people management or tech lead experience for a team shipping production data solutions, required • Strong hands-on experience with modern cloud data platforms, with Snowflake preferred and Databricks or comparable platforms relevant • Hands-on experience with dbt for modular, testable, well documented transformation models • Experience with ingestion and orchestration tooling such as Fivetran, Airflow, or equivalent • Experience building governed BI and semantic layers in Sigma Computing or Power BI • Track record migrating from legacy SSIS, SSRS, SSAS, or comparable stacks to a modern cloud data platform, including metric translation and reconciliation • Strong SQL and dimensional data modeling skills for analytical and financial datasets • Python experience for pipeline tooling, automation, and integration • Experience with Azure and/or AWS cloud-native data architecture • Experience integrating enterprise systems via APIs, file based transfers, or event driven workflows • Experience implementing data quality, lineage, governance, and audit controls • Exposure to applied AI or LLM enabled workflows in a production setting, preferred • Track record of contributing to technical strategy and architectural direction, not only delivery on assigned tasks
• Competencies & Attributes • True architect’s mindset. Selects the right technology for each problem and is willing to learn and adopt new platforms rather than defaulting to a fixed stack. • Data trust mindset. Treats every published metric as a commitment to its consumers, and builds certification, lineage, and quality in from the start. • Enterprise understanding. Articulates the path forward in handling the complexity and scale of a financial firm’s data and reporting obligations. • Stakeholder fluency. Communicates clearly with both technical and non-technical audiences and earns the trust of senior Finance leaders. • Engineering leadership. Sets technical direction by example and raises the bar through code review and mentorship. • Builder’s instinct under ambiguity. Turns a vague reporting requirement into a working, certified data product and measures progress in shipped pipelines.
• Benefits/Compensation The compensation range for this role is specific to Washington, DC, and takes into account a wide range of factors including but not limited to the skill sets required/preferred; prior experience and training; licenses and/or certifications.
• The anticipated base salary range for this role is $170,000 to $190,000.
• In addition to the base salary, the hired professional will enjoy a comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits and various wellness programs. Additionally, the hired professional may also be eligible to participate in an annual discretionary incentive program, the award of which will be dependent on various factors, including, without limitation, individual and organizational performance.
• Due to the high volume of candidates, please be advised that only candidates selected for an interview will be contacted by Carlyle.
• Education & Certifications
• Bachelor’s degree, required
• Professional Experience
• 10+ years of overall relevant data engineering or data architecture experience, required
• Demonstrated people management or tech lead experience for a team shipping production data solutions, required
• Hands-on experience with dbt for modular, testable, well documented transformation models
• Experience with ingestion and orchestration tooling such as Fivetran, Airflow, or equivalent
• Experience building governed BI and semantic layers in Sigma Computing or Power BI
• Track record migrating from legacy SSIS, SSRS, SSAS, or comparable stacks to a modern cloud data platform, including metric translation and reconciliation
• Strong SQL and dimensional data modeling skills for analytical and financial datasets
• Python experience for pipeline tooling, automation, and integration
• Experience with Azure and/or AWS cloud-native data architecture
• Experience integrating enterprise systems via APIs, file based transfers, or event driven workflows
• Experience implementing data quality, lineage, governance, and audit controls
• Track record of contributing to technical strategy and architectural direction, not only delivery on assigned tasks
• Competencies & Attributes
• True architect’s mindset. Selects the right technology for each problem and is willing to learn and adopt new platforms rather than defaulting to a fixed stack.
• Data trust mindset. Treats every published metric as a commitment to its consumers, and builds certification, lineage, and quality in from the start.
• Enterprise understanding. Articulates the path forward in handling the complexity and scale of a financial firm’s data and reporting obligations.
• Stakeholder fluency. Communicates clearly with both technical and non-technical audiences and earns the trust of senior Finance leaders.
• Engineering leadership. Sets technical direction by example and raises the bar through code review and mentorship.
• Builder’s instinct under ambiguity. Turns a vague reporting requirement into a working, certified data product and measures progress in shipped pipelines.
• Benefits/Compensation

Who We Are

Preferred Qualifications

• Concentration in computer science, engineering, information systems, or a related quantitative field, preferred
• Master’s degree, preferred
• 7+ years in financial services such as private equity, asset management, investment banking, hedge fund, or fund administration, preferred
• Strong hands-on experience with modern cloud data platforms, with Snowflake preferred and Databricks or comparable platforms relevant
• Exposure to applied AI or LLM enabled workflows in a production setting, preferred
• The compensation range for this role is specific to Washington, DC, and takes into account a wide range of factors including but not limited to the skill sets required/preferred; prior experience and training; licenses and/or certifications.