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