Corbin Advisors
Job Description
Data Analytics Engineer
As a Data Analytics Engineer at Corbin, you will play a pivotal role in bridging business needs and technical execution. You’ll partner closely with client‑facing teams, internal operations, and our systems architecture team to lead design, implement, and optimize data‑driven solutions that reduce manual processes and enhance decision‑making. This is a hands‑on role focused on building and maintaining relational databases, engineering data pipelines, and enabling analytics through cloud data platforms. The ideal candidate will have a strong SQL foundation, exposure to cloud data platforms, and a working knowledge of capital markets. If you’re eager to learn, solve complex problems, and contribute to scalable data systems, this role is for you.
Core Responsibilities:
Documentation: In partnership with the Business Analyst, translate business requirements into technical specifications, process maps, and data flow diagrams to guide solution design and implementation.
Relational Database Management: Support the design and maintenance of relational databases in Snowflake, DOMO, or other tools
Data Flows: Collaborate with the systems architect and business analyst to design and maintain secure, reliable data flows between cloud systems, leveraging APIs and automated processes.
ETLS and Data Pipelines: Build, deploy, and manage ETL/ELT pipelines that ensure clean, structured, and reliable data for reporting and analytics.
Data Visualization: Partner with functional teams to develop and maintain automated dashboards and reporting solutions to support business intelligence and client reporting.
Collaboration: Work closely with cross‑functional teams to create and implement solutions that support the organization’s evolving data needs
Data Analytics: Interpreting datasets to uncover trends and insights
Data Governance: Advocate, implement, and enforce best practices around data quality, security, and governance to ensure compliance and reliability across platforms.
API Integration: Lead integration and development with additional tools to support business needs
Requirements
Strong analytical and critical thinking skills with the ability to translate business needs into technical solutions
Initiative‑taking, detail‑oriented, and passionate about innovation and process improvement
Hands‑on experience with relational databases (preferably Snowflake)
Proficiency in SQL, with the ability to design and optimize queries for performance
Experience building ETL/ELT pipelines and automated reporting dashboards (DOMO, Tableau, or similar)
Familiarity with RESTful APIs and data integration techniques
Excellent communication and interpersonal skills, with the ability to engage both technical and non‑technical stakeholders
Ability to work in a fast‑paced, dynamic environment and manage multiple projects effectively, comfort working in agile, cross‑functional teams
Cloud Data Platforms: Proficiency with cloud‑based data warehouses and relevant tools.
Business Acumen: Understanding how to align data solutions with business goals and providing actionable insight
Qualifications
Bachelor’s degree in Computer Science or related field
3‑8 years relevant work experience
Background in capital markets, financial services, or investor relations preferred
Experience with cloud data platforms (Snowflake, AWS, Azure, or GCP)
Exposure to scripting languages (Python, JavaScript, etc.) for data transformation and automation
Hands‑on experience with relational databases (preferably Snowflake)
Proficiency in SQL, with the ability to design and optimize queries for performance
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As a Data Analytics Engineer at Corbin, you will play a pivotal role in bridging business needs and technical execution. You’ll partner closely with client‑facing teams, internal operations, and our systems architecture team to lead design, implement, and optimize data‑driven solutions that reduce manual processes and enhance decision‑making. This is a hands‑on role focused on building and maintaining relational databases, engineering data pipelines, and enabling analytics through cloud data platforms. The ideal candidate will have a strong SQL foundation, exposure to cloud data platforms, and a working knowledge of capital markets. If you’re eager to learn, solve complex problems, and contribute to scalable data systems, this role is for you.
Core Responsibilities:
Documentation: In partnership with the Business Analyst, translate business requirements into technical specifications, process maps, and data flow diagrams to guide solution design and implementation.
Relational Database Management: Support the design and maintenance of relational databases in Snowflake, DOMO, or other tools
Data Flows: Collaborate with the systems architect and business analyst to design and maintain secure, reliable data flows between cloud systems, leveraging APIs and automated processes.
ETLS and Data Pipelines: Build, deploy, and manage ETL/ELT pipelines that ensure clean, structured, and reliable data for reporting and analytics.
Data Visualization: Partner with functional teams to develop and maintain automated dashboards and reporting solutions to support business intelligence and client reporting.
Collaboration: Work closely with cross‑functional teams to create and implement solutions that support the organization’s evolving data needs
Data Analytics: Interpreting datasets to uncover trends and insights
Data Governance: Advocate, implement, and enforce best practices around data quality, security, and governance to ensure compliance and reliability across platforms.
API Integration: Lead integration and development with additional tools to support business needs
Requirements
Strong analytical and critical thinking skills with the ability to translate business needs into technical solutions
Initiative‑taking, detail‑oriented, and passionate about innovation and process improvement
Hands‑on experience with relational databases (preferably Snowflake)
Proficiency in SQL, with the ability to design and optimize queries for performance
Experience building ETL/ELT pipelines and automated reporting dashboards (DOMO, Tableau, or similar)
Familiarity with RESTful APIs and data integration techniques
Excellent communication and interpersonal skills, with the ability to engage both technical and non‑technical stakeholders
Ability to work in a fast‑paced, dynamic environment and manage multiple projects effectively, comfort working in agile, cross‑functional teams
Cloud Data Platforms: Proficiency with cloud‑based data warehouses and relevant tools.
Business Acumen: Understanding how to align data solutions with business goals and providing actionable insight
Qualifications
Bachelor’s degree in Computer Science or related field
3‑8 years relevant work experience
Background in capital markets, financial services, or investor relations preferred
Experience with cloud data platforms (Snowflake, AWS, Azure, or GCP)
Exposure to scripting languages (Python, JavaScript, etc.) for data transformation and automation
Hands‑on experience with relational databases (preferably Snowflake)
Proficiency in SQL, with the ability to design and optimize queries for performance
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