Solution Architect – Advanced Analytics - CONTRACT - 100% Remote - US Based

CoEnterprise, LLC.; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

A leading company is seeking a Solution Architect for Advanced Analytics to design cloud-native analytics architectures. This role requires strong consultative skills to assess client needs and lead implementation from data ingestion to reporting and machine learning. The ideal candidate will communicate technical concepts effectively and mentor teams to ensure best practices.

Qualifications

• 7+ years in data and analytics, with 3+ years in a lead or architect role.
• Experience designing and implementing complex analytics platforms.

Responsibilities

• Design scalable, secure, and cost-efficient data platforms on cloud infrastructure.
• Collaborate with stakeholders to define business goals and translate them into technical solutions.
• Guide the selection and integration of data warehousing and visualization platforms.

Skills

Communication

Analytical Thinking

Consultative Skills

Education

Bachelor’s degree in Computer Science

Master’s degree in a technical or data discipline

Tools

SQL

Python

Spark

Airflow

Databricks

Snowflake

Kafka

Kinesis

Job description

Solution Architect – Advanced Analytics - CONTRACT - 100% Remote - US Based

CoEnterprise is an award-winning B2B software and professional services company headquartered in New York City. Founded in 2010, CoEnterprise delivers Data & Analytics solutions and services that transform how companies connect and do business. We value collaboration, ownership, and excellence in our work and client relationships.

As a Solution Architect – Advanced Analytics, you will lead the design and delivery of cloud-native analytics architectures for enterprise clients. This highly technical role requires strong consultative and communication skills to assess client needs, define solutions, and lead implementation across the data lifecycle—from ingestion to reporting and machine learning. You will also articulate the business value and ROI of these solutions, bridging IT and strategic business outcomes.

Key Responsibilities:

• Design scalable, secure, and cost-efficient data platforms on cloud infrastructure (AWS, Azure, GCP).
• Collaborate with stakeholders to define business goals and translate them into technical solutions.
• Develop and implement data pipelines, modeling strategies, and analytics workflows using modern tools.
• Guide the selection and integration of data warehousing, lakehouse, and visualization platforms.
• Present architectural proposals and technical recommendations, emphasizing business impact and measurable outcomes.
• Translate technical trade-offs into business language for informed decision-making.
• Support clients in aligning analytics architectures with KPIs and compliance needs.
• Contribute to sales activities like technical scoping, RFP responses, and solution documentation.
• Mentor consultants and data engineers to ensure best practices.

Technical Stack (Experience Preferred):

• Data Engineering: dbt, Spark, Airflow, Databricks, Snowflake, Delta Lake, Data Vault, Canonical Data Model
• Streaming: Kafka, Kinesis, Event Hubs
• Storage & Warehousing: S3, ADLS, BigQuery, Synapse, Snowflake
• Programming: SQL (advanced), Python, PySpark
• Security & Governance: IAM, RBAC, encryption, compliance (HIPAA, SOC 2, GDPR)

Qualifications:

Required:

• Bachelor’s degree in Computer Science, Data Engineering, or related field.
• 7+ years in data and analytics, with 3+ years in a lead or architect role.
• Experience designing and implementing complex analytics platforms.
• Ability to communicate technical concepts to business audiences, focusing on value and impact.
• Experience in consulting or professional services with client-facing responsibilities.

Preferred:

• Master’s degree in a technical or data discipline.
• Certifications in AWS, Azure, or GCP.
• Experience aligning analytics with business strategies like digital transformation.
• Exposure to MLOps and ML model integration into data pipelines.

Soft Skills:

• Strong communicator capable of translating technical details into business language.
• Confident, consultative, and able to influence stakeholders.
• Analytical, innovative, and practical thinker.
• Proactive, self-directed, and committed to continuous learning.