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

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