Data & Analytics Engineer at ABOUT HEALTHCARE INC

Saint Paul, Minnesota, United States -

Full Time

Start Date

Immediate

Expiry Date

01 Jul, 26

Salary

0.0

Posted On

02 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Business Intelligence, SQL, Data Modeling, Data Transformation, Tableau, Data Quality, ETL, Analytics, Cloud Platforms, Data Governance, Problem Solving, Collaboration, Documentation, Dashboard Development, Data Analysis

Industry

Software Development

Description

SUMMARY: The Data and Analytics Engineer is a hybrid role responsible for delivering end-to-end analytics solutions—from data transformation and modeling to business intelligence and visualization. This role combines data engineering and reporting expertise to ensure data is accurate, well-structured, and delivered through intuitive dashboards and analytics tools that drive business decisions. Partnering closely with Intelligence, Data Engineering, and platform teams, this role builds and maintains scalable data models, curated datasets, and analytical views within the data platform, while also designing and developing dashboards, reports, and self-service analytics solutions. The Data and Analytics Engineer bridges technical data systems and business needs, owning the transformation and reporting layers while contributing to, but not owning, upstream pipeline and infrastructure design. ESSENTIAL FUNCTIONS: This class specification lists the major duties and requirements of the job and is not all-inclusive. Incumbent(s) may be expected to perform job-related duties other than those contained in this document and may be required to have specific job-related knowledge and skills. * Business Intelligence & Analytics Delivery: * Develop and maintain high-impact dashboards and reports using Tableau or similar tools. Translate business requirements into technical solutions by defining metrics, calculations, and aggregations. Support ad hoc analysis and ensure reporting outputs are aligned with trusted data models. * Translate business requirements into clear metrics, KPIs, and visualizations, ensuring alignment with organizational goals. * Partner with stakeholders to define reporting needs and deliver actionable insights and analysis. * Optimize report performance, usability, and adoption across business teams. * Data Modeling & Transformation: Design, build, and maintain scalable data models and transformation logic using SQL and modern data tooling (e.g., dbt). Develop standardized, reusable datasets and data marts that support consistent analytics across the organization. Optimize data structures for performance, scalability, and ease of use. * Data Pipeline & Quality Ownership: Partner with Data Engineering to support the design, development, and monitoring of data pipelines. Implement data validation rules, testing frameworks, and quality checks to ensure accuracy and reliability of data assets. Troubleshoot pipeline and data issues, performing root cause analysis and coordinating resolutions across systems. * Data Governance & Documentation: Document data models, business logic, and field-level definitions to ensure transparency and usability. Enforce data standards, naming conventions, and governance best practices. Support compliance with applicable laws, regulations, and data security requirements. * Platform Enablement & Self-Service: Enable self-service analytics by delivering curated, analytics-ready datasets and educating users on how to leverage them effectively. Support BI platform administration activities such as access management, content publishing, and performance optimization. * Cross-Team Collaboration: Partner with Intelligence, Product, Engineering, and Business stakeholders to understand data needs and deliver scalable solutions. Act as a bridge between upstream data engineering and downstream analytics, ensuring alignment and consistency across the data ecosystem. * Tableau Administration: Assist in managing Tableau environments, including user access, permissioning, content publishing, and basic server/site administration, as needed in collaboration with Sr Reporting & BI Developer. * Source Data Analysis & QA: Analyze source systems to understand data flows, structures, and anomalies that impact modeling. Ensures the accuracy of operational databases, reports, and related details through audits, queries, and operational reviews; works with teams to resolve discrepancies * Issue Resolution: Provide research, feedback to resolve management and customer questions and requirements; assists with receiving customer feedback and coordinating resources and responses as required. Troubleshoot and resolve data transformation, modeling, or pipeline issues in collaboration with broader data teams. * Process Improvement: Analyze system data to provide insights, draw conclusions, and provide recommendations for improving policies, data pipelines, modeling standards, and workflows/operations. Contribute to the efficiency and effectiveness of the department's service to its customers by offering suggestions and directing or participating as an active member of a work team. Train others in related policies and procedures, as needed. * Continuous Learning: Stay current on new tools, technologies, and best practices in data engineering, modeling, and analytics enablement. * Perform other duties as assigned. QUALIFICATIONS: To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Need to Have: * Bachelor’s Degree in Computer Science, Information Systems, Data Analytics, or related experience * 4–6 years of experience in analytics engineering, data engineering, business intelligence, or related roles * Strong experience working with large, complex datasets and cloud data platforms (e.g., Snowflake, Redshift, SQL Server) Nice to Have: * Prior experience working in a private equity-funded organization * Healthcare technology experience * Understanding of data governance principles, including naming conventions and lineage * Experience working with Git or version control in a collaborative environment * Knowledge of cloud ecosystems (e.g., AWS, Azure, GCP) * Master's degree in Information Technology or related field Required Knowledge and Skills Required Knowledge: * Advanced principles of data modeling (dimensional and normalized) and semantic layer design * Understanding of ETL/ELT processes and modern data pipeline architectures * Data governance concepts including lineage, naming conventions, and data standards * Principles of data quality, validation, and testing methodologies * Understanding of business intelligence platforms and analytics ecosystems * Knowledge of applicable laws, codes, regulations, and data governance requirements (e.g., HIPAA) Required Skills: * Advanced proficiency in SQL for data transformation and analysis * Experience with data transformation tools (e.g., dbt, stored procedures, SQL scripts) * Ability to design, build, and optimize scalable data models * Ability to perform advanced data engineering tasks across ingestion, transformation, and delivery layers * Strong data quality practices with attention to detail and commitment to accuracy * Ability to document data models, field logic, and lineage in a clear, business-friendly format * Experience developing, consulting on, and optimizing dashboard and report packages (Tableau, Power BI, or similar) * Experience overseeing and supporting business intelligence and data analytical systems (e.g., semantic layer, BI platforms, access/permissions, content lifecycle) * Proficiency using standard, customized, and complex data analytics tools and techniques * Strong analytical, problem-solving, and communication skills; ability to translate complex data into actionable insights * Ability to interpret, apply, and explain applicable laws, codes, and regulations in practical scenarios PHYSICAL/MENTAL REQUIREMENTS: The physical demands described herein are representative of those that must be met by an employee to successfully perform the essential functions of the job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Mobility to work in an office setting, use standard office equipment and stamina to sit for extended periods of time; strength to lift and carry up to 10 pounds; vision to read printed materials and computer screens; and hearing and speech to communicate in person or over the telephone. Travel as needed to support company and customer initiatives. Work on Site at our St Paul office may be required and ABOUT reserves the right to change the location of the role at any time. This role may involve work on federal government contracts that require additional federal background investigations, training, and federal badging. As such, you may be required to submit personal information to the government and be fingerprinted and photographed at your local Department of Veteran Affairs Medical Center. ABOUT Healthcare is also an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status, sexual orientation, gender identity or expression, marital status, genetic information, or any other characteristic protected by law.

Responsibilities

The Data and Analytics Engineer is responsible for delivering end-to-end analytics solutions, including data transformation, modeling, and visualization. This role involves building scalable data models and dashboards while ensuring data accuracy and alignment with business needs.