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.

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.

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.

Vista is a leading global investment firm that exclusively invests in enterprise software, data and technology-enabled organizations across private equity, permanent capital, credit and public equity strategies, bringing an approach that prioritizes creating enduring market value for the benefit of its global ecosystem of investors, companies, customers and employees. Vista’s investments are anchored by a sizable long-term capital base, experience in structuring technology-oriented transactions and proven, flexible management techniques that drive sustainable growth. Vista believes the transformative power of technology is the key to an even better future – a healthier planet, a smarter economy, a diverse and inclusive community and a broader path to prosperity. Further information is available at vistaequitypartners.com. Follow Vista on LinkedIn, @Vista Equity Partners, and on X, @Vista_Equity.