Senior Solutions Architect - Data Platforms

Title: Senior Solutions Architect - Databricks

Focus: Data Engineering and Data Platforms

Location: Remote, US-based (EST preferred)

Compensation Range: $175,000 - $200,000

Reports to: Head of Solutions Architecture

We are seeking an experienced Senior Solutions Architect to drive Data Engineering and Data Platform initiatives, aligning business needs with technical solutions. This role will be responsible for designing, implementing, and optimizing scalable data platforms while ensuring data reliability, governance, and analytics enablement. The ideal candidate will have a deep understanding of data engineering, cloud platforms, and data architecture while effectively collaborating with stakeholders to deliver business value.

Solution Strategy and Architecture:

• Define and drive the data engineering and platform strategy, ensuring alignment with business goals.
• Architect scalable, secure, and cost-effective data platforms on cloud and hybrid environments.
• Develop frameworks for data integration, ingestion, transformation, and storage across diverse sources.
• Ensure data solutions support real-time and batch processing needs for analytics and reporting
• Drive data platform modernization efforts from On-Prem to Cloud platform

Data Engineering and Platform Development:

• Lead the design and development of data pipelines, ETL/ELT processes, and data lake/data warehouse solutions.
• Optimize data storage, indexing, and query performance to improve accessibility and efficiency.
• Implement data governance, security, and compliance best practices.
• Evaluate and recommend modern data stack tools (e.g., Databricks, Snowflake, BigQuery, Apache Spark, Kafka).

Business and Stakeholder Engagement:

• Collaborate with business teams, product managers, and data scientists to understand data needs and drive adoption of platform solutions.
• Act as a bridge between technical teams and business units, translating business requirements into scalable data solutions.
• Provide guidance on best practices for data engineering, analytics enablement, and AI/ML integration.

Operational Excellence and Innovation:

• Ensure data quality, reliability, and availability through monitoring and automated testing.
• Drive continuous improvement of data platforms using emerging technologies and methodologies.
• Establish and enforce data governance policies, metadata management, and documentation standards.
• Lead efforts to enhance self-service data capabilities for business users.

Required Skills and Qualifications:

• 10+ years of experience in data engineering, data platform architecture, or cloud-based data solutions.
• Strong understanding of big data processing frameworks (e.g., Spark, Hadoop) and cloud data platforms (AWS, Azure).
• Hands-on experience with modern data architectures, including data lakes, data warehouses, and lakehouses.
• Deep knowledge of ETL/ELT tools, data modelling, data foundations.
• Knowledge of data governance, lineage, cataloging, and compliance frameworks (e.g., GDPR, CCPA).
• Strong problem-solving skills with an ability to balance technical and business priorities.
• Excellent communication and stakeholder management skills.
• Experience with Databricks, Snowflake, or Synapse Analytics.
• Familiarity with ML platforms and MLOps best practices.
• Certified in AWS, Azure, GCP, Databricks or Snowflake

Eames Consulting is acting as an Employment Agency in relation to this vacancy.