This position is remote in USA preferably in Dallas, Texas and must eligible and authorized with valid documents to work in the United States. No recruiting agencies please.

REQUIRED SKILLS & EXPERIENCE:

• 5+ years in Data Engineering, Cloud Infrastructure, or similar roles focused on data platforms.
• Deep experience with at least one cloud platform (AWS, Azure, GCP), including computer, storage, and data services.
• Strong skills in SQL and Python for data processing and automation.
• Proficiency in data pipeline tools (e.g., Apache, Airflow, dbt, Kafka, Spark, Flink).
• Experience with streaming data processing and real-time analytics use cases.
• Hands-on experience with Infrastructure as Code tools (e.g., Terraform, CloudFormation).
• Familiarity with containerization and orchestration (Docker, Kubernetes).
• Understanding of data governance, access control, encryption and compliance best practices (e.g., HIPAA, SOC2).
• Experience supporting machine learning or working alongside data science teams.

PREFERRED QUALIFICATIONS:

• Experience with CI/CD pipelines and DevOps for data systems.
• Familiarity with data observability and monitoring tools (e.g., ELK, Datadog, Prometheus).
• Exposure to data catalogs or lineage tools (e.g., Amundsen, DataHub, Collibra).
• Experience in environments with customer behavior analytics or personalization use cases.

Location & Hours:

• This position is remote within the USA. Hours 8:00- 5:00CST

Salary Range: $150-$170

ABOUT THE ROLE:

We are seeking a talented and experienced Data Platform Engineer to build and scale the infrastructure that powers our enterprise analytics and machine learning capabilities. This individual will play a critical role in designing, developing, and maintaining the cloud-based architecture and data pipelines that support real-time and near real-time insights across the organization.
You will collaborate with analysts, data scientists, and business teams to ensure the right data is available, secure, and actionable, from ingestion through transformation to consumption. If you are passionate about building systems that turn raw data into powerful business intelligence and machine learning capabilities, we want to hear from you.

KEY RESPONSIBILITIES:

• Design, implement, and maintain cloud-native data infrastructure to support analytics and machine learning workloads.
• Build and optimize real-time and batch data pipelines for ingesting and transforming customer and operational data.
• Deploy and manage data lake and data warehouse platforms such as Snowflake, Redshift, BigQuery, or Databricks.
• Enable and support machine learning operations (MLOps) including feature stores, model pipelines, and production model serving.
• Use infrastructure as code (IaC) tools (e.g., Terraform, CloudFormation) to automate infrastructure provisioning and management.
• Implement data quality checks, observability, and lineage tracking across data workflows.
• Monitor and ensure performance, security, and scalability of the data platform.
• Collaborate with cross-functional teams to understand data requirements and deliver scalable, efficient solutions.