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.

Position Overview 

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. 

Key Responsibilities 

Architecture & Design 

  • 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 

Data Platform Management 

  • 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 (BigQuery, Dataflow, Dataproc) services 
  • Implement containerized data processing solutions 

Data Integration & Pipeline Development 

  • Design robust ETL/ELT pipelines for batch and real-time data processing 
  • Architect data replication strategies across heterogeneous systems 
  • Develop data ingestion frameworks for structured and unstructured data sources 
  • Implement CDC solutions and event-driven architecture for real-time analytics 

Data Modeling & 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 

Business Intelligence & Data Governance 

  • 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 

Leadership & Collaboration 

  • 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 

Required Qualifications 

Technical Expertise 

  • 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, CloudFormation, or similar tools 

Data Management 

  • 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 

Professional Background 

  • 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 

Preferred Qualifications 

  • 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 DevOps practices 

 

Executive Management

Plano, TX

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