[ref. d35052716] Austin - Data Architect

Position Summary:

At Vista, we are redefining how data is leveraged to drive business growth and innovation. We are seeking a hands-on Data Architect who will both lead the design and actively participate in the development of our robust data architecture.

As a Data Architect, you will work directly with data engineers and cross-functional teams, playing a critical role in building and optimizing the data infrastructure that powers real-time analytics and advanced business insights. This is a hands-on role where you will be coding, testing, and troubleshooting alongside the team, ensuring high-quality delivery at all levels of the data stack.

Responsibilities:

Hands-On Development: Architect, design, and develop data pipelines and infrastructure components, writing high-quality code and ensuring solutions are scalable, secure, and efficient.

Data Integration: Design and develop integrations between multiple data sources, ensuring seamless data availability across the organization. Troubleshoot issues as they arise, providing technical expertise and solutions.

Cloud Infrastructure: Build and optimize cloud-based data platforms (AWS, Azure, GCP). This includes hands-on work in managing resources such as data lakes, data warehouses, and real-time streaming platforms.

Real-Time Data Solutions: Architect and implement real-time data pipelines for high-throughput, low-latency processing using technologies like Apache Kafka, Kinesis, or Dataflow.

Data Quality & Validation: Establish and implement automated data validation and testing frameworks, ensuring data accuracy, completeness, and reliability.

Cross-Functional Collaboration: Work closely with data engineers and business stakeholders to translate business needs into technical solutions. Be a hands-on contributor in building prototypes, proof of concepts, and production systems.

Data Modeling: Design and implement data models for both operational and analytical use cases, ensuring models are optimized for performance and scalability in a cloud environment.

Data Governance: Implement and enforce data governance best practices, including metadata management, data lineage, and security policies. Ensure compliance with regulatory standards and internal data policies.

Automation & Infrastructure as Code (IaC): Leverage Infrastructure as Code tools (Terraform) to automate deployment and management of cloud infrastructure. Design CI/CD pipelines to automate testing and deployment of data pipelines and infrastructure.

Mentorship & Leadership: While being hands-on, you will also provide technical leadership, mentoring junior team members and fostering a culture of collaboration and knowledge sharing.

Qualifications:

Experience: 7+ years of experience in data engineering or data architecture, with at least 3 years in a hands-on technical leadership or architecture role.

Hands-On Expertise: Demonstrated ability to write production-level code in Python, SQL, and big data frameworks like Apache Spark, Hadoop, or similar. Must be comfortable jumping into technical problems and building solutions.

Cloud Data Platforms: Expert-level experience with cloud platforms (AWS, Azure, GCP). Hands-on experience with tools like Redshift, BigQuery, Snowflake, or Synapse.

Data Pipeline & Orchestration Tools: Hands-on experience with building and optimizing data pipelines using tools like Apache Airflow, Azure Data Factory, dbt, Fivetran and similar ETL/ELT frameworks.

Real-Time Data: Experience with real-time data streaming platforms (e.g., Kafka, Kinesis, Flink), with a strong focus on building and maintaining low-latency, high-throughput data systems.

Data Modeling & Design: Extensive experience in designing and implementing data models for both operational databases and data warehouses, including dimensional modeling and data vault techniques.

Agile Methodologies: Proven ability to work in an Agile environment, balancing hands-on technical work with strategic decision-making to rapidly deliver high-quality data solutions.

Data Security & Governance: Deep understanding of security best practices, including encryption, authentication, and role-based access controls for large-scale data platforms.

Preferred Qualifications

Machine Learning Support: Hands-on experience designing data solutions that support machine learning workflows, including feature stores and real-time data feeds for model inference.

Company Overview:

Further information is available at vistaequitypartners.com. Follow Vista on LinkedIn, @Vista Equity Partners, and on X, @Vista_Equity.