Data Solutions Architect

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We’re hiring passionate builders to shape the future of industrial intelligence.

We are seeking an experienced Data Solutions Architect to design, implement, and optimize enterprise-scale data architectures across cloud platforms. This role requires deep expertise in modern data stack technologies including Databricks, Snowflake, and AWS/GCP cloud services. The ideal candidate will drive data strategy, ensure robust governance frameworks, and enable advanced analytics capabilities that support business-critical decision making.

• Design scalable, secure data architectures on AWS and GCP cloud platforms
• Develop data architecture blueprints for data lakes, warehouses, and streaming solutions
• Create technical specifications and establish architectural standards and best practices
• Evaluate and recommend emerging technologies to enhance the data ecosystem

• Lead Databricks implementation for advanced analytics and machine learning workloads
• Design and optimize Snowflake data warehouse architectures for performance and cost
• Architect multi-cloud solutions using AWS (S3, Redshift, Glue, EMR) and GCP (Big Query, Dataflow, Dataproc) services
• Implement containerized data processing solutions
• Design robust ETL/ELT pipelines for batch and real-time data processing
• Develop data ingestion frameworks for structured and unstructured data sources
• Implement CDC solutions and event-driven architecture for real-time analytics

• Develop logical and physical data models optimized for analytical workloads
• Design dimensional modeling and data vault solutions for enterprise data warehouses
• Architect self-service analytics platforms for business users
• Create domain-specific data marts and advanced modeling techniques

• Architect BI solutions integrating with platforms like Tableau, Power BI, and Looker
• Implement comprehensive data governance frameworks ensuring quality, lineage, and metadata management
• Design data privacy solutions compliant with GDPR, CCPA, and regulatory requirements
• Establish role-based access controls, data classification, and security frameworks
• Partner with stakeholders to translate business requirements into technical solutions
• Provide technical leadership and mentorship to development teams
• Drive architectural reviews and present designs to executive leadership
• Collaborate with data engineers, analysts, and scientists for optimal platform performance

• Cloud Platforms: 5+ years of hands-on experience with AWS and/or GCP data services
• Databricks: 3+ years designing and implementing Databricks solutions for analytics and ML workloads
• Snowflake: 3+ years architecting Snowflake data warehouse solutions
• Programming:
  Proficiency in Python, SQL, Scala, and/or Java for data processing applications
• Big Data Technologies:
  Experience with Apache Spark, Kafka, Airflow, and other distributed computing frameworks
• Infrastructure as Code:
  Proficiency with Terraform, Cloud Formation, or similar tools

• Data Integration:
  Extensive experience with ETL/ELT tools and frameworks
• Data Modeling:
  Strong background in dimensional modeling, data vault, and modern data architecture patterns
• Data Governance:
  Proven experience implementing data quality, lineage, and metadata management solutions
• Analytics:
  Experience architecting solutions for advanced analytics, machine learning, and AI workloads

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field
• 7+ years of experience in data architecture, engineering, or related roles
• Strong project management skills with experience leading complex, multi-stakeholder initiatives
• Excellent communication skills with ability to present technical concepts to non-technical audiences

• Cloud certifications (AWS Solutions Architect, GCP Professional Data Engineer, or similar)
• Experience with additional cloud platforms (Azure)
• Knowledge of machine learning operations (MLOps) and AI/ML lifecycle management
• Experience with real-time analytics and streaming technologies
• Background in financial services, healthcare, or other highly regulated industries
• Familiarity with open-source data technologies and frameworks
• Experience with agile development methodologies and Dev Ops practices