Senior Data Architect

Orangepeople•Plano, TX

20h

About The Position

We are currently hiring an experienced Senior Data Architect to join our team. We are looking for a strong, hands-on architect to design and deliver scalable enterprise data solutions and drive improvements across data integration, data quality, data delivery, and modern cloud data platforms. The ideal candidate will bring deep expertise in Databricks, AWS, modern data architecture, and DevOps/Infrastructure as Code, combined with strong architecture leadership and the ability to partner with senior management, engineering teams, and enterprise stakeholders.

Requirements

10+ years of experience designing and developing enterprise data platforms, data warehouses, ETL/ELT pipelines, and large-scale data solutions.
Strong hands-on experience with Databricks and modern cloud-based data platforms.
Strong experience architecting and delivering enterprise solutions on AWS.
Strong understanding of modern data architecture, including data lakes, lakehouses, data warehouses, data integration, and scalable data processing patterns.
Experience with Apache Spark and large-scale data processing.
Strong experience with SQL and at least one relevant programming/scripting language such as Python, Java, Scala, or Bash.
Strong understanding and practical experience with DevOps, CI/CD, and infrastructure automation.
Experience with Infrastructure as Code (IaC) using Terraform, AWS CloudFormation, or comparable technologies.
Proven experience providing architecture and technical leadership for complex enterprise data initiatives.
Ability to partner with senior management, enterprise architects, engineering teams, and business stakeholders to define and drive technical solutions.
Exceptional written and verbal communication skills with the ability to communicate complex architecture decisions and influence stakeholders at multiple levels.

Nice To Haves

Experience with additional AWS data technologies such as EMR, Redshift, S3, Lambda, Kinesis, EC2, SNS, ElastiCache/Redis, and Airflow.
Experience with Snowflake or additional cloud data platforms.
Exposure to GCP technologies, including BigQuery, Google Cloud Storage, Dataproc, and Pub/Sub.
Experience designing batch, CDC, and real-time streaming ingestion architectures, including technologies such as Kafka and Kinesis.
Experience with DevOps and automation tools such as Jenkins, Ansible, Chef, XL Release, XL Deploy, or comparable modern tooling.
Knowledge of microservices, containers, RESTful APIs, and cloud-native architecture patterns.
Experience working across multiple cloud platforms.
Experience supporting or leading large-scale, complex enterprise transformation initiatives.

Responsibilities

Serve as a key technical partner to Senior Management, Data & Analytics teams, and Enterprise Architects, driving solutions aligned with the organization's Data & Analytics strategy.
Define and drive enterprise data architecture, architectural patterns, technical standards, and strategic roadmaps for modern data platforms.
Design scalable, highly available, high-performing, and reliable data architectures supporting data integration, processing, reporting, and analytics.
Provide hands-on architecture leadership across Databricks, AWS, cloud data platforms, and DevOps/Infrastructure as Code.
Architect and guide the development of data platforms, data warehouses/lakehouse solutions, and ETL/ELT pipelines supporting enterprise-scale workloads.
Evaluate technology alternatives and communicate architectural decisions, business benefits, risks, and technical implications to senior stakeholders and enterprise architects.
Drive the strategic vision and roadmap for modern cloud and data architecture in support of Data & Analytics initiatives.
Establish and promote DevOps, Infrastructure as Code (IaC), CI/CD, and automation best practices across data platform environments.
Provide technical leadership, architecture guidance, and mentorship to engineering teams while collaborating across application, infrastructure, cloud, security, and business teams.
Participate in OP monthly team meetings and participate in team-building efforts.
Contribute to OP technical discussions, peer reviews, etc.
Contribute content and collaborate via the OP-Wiki/Knowledge Base.
Provide status reports to OP Account Management as requested.