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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