Data Infrastructure Engineer - Remote

Overview

Worth AI, a leader in the computer software industry, is looking for a talented and experienced Data Infrastructure Engineer to join their innovative team. At Worth AI, we are on a mission to revolutionize decision-making with the power of artificial intelligence while fostering an environment of collaboration, and adaptability, aiming to make a meaningful impact in the tech landscape. Our team values include extreme ownership, one team and creating raving fans both for our employees and customers.

In Short

• Design, build, and maintain scalable and resilient data infrastructure in a cloud environment (AWS, Azure, or GCP).
• Develop and maintain ETL/ELT pipelines using orchestration tools such as Airflow, Dagster, or dbt.
• Optimize data workflows for reliability, performance, and cost efficiency across structured and unstructured datasets.
• Manage data lake and data warehouse environments (e.g., Snowflake, BigQuery, Redshift, Delta Lake).
• Ensure data security, privacy, and compliance, including role-based access control, data encryption, and audit logging.
• Collaborate with data scientists, analysts, and product teams to ensure data accessibility, accuracy, and availability.
• Support real-time and batch data processing frameworks, including Kafka, Spark, Flink, or similar tools.
• Monitor, troubleshoot, and improve the observability and performance of data systems using tools like Prometheus, Grafana, or Datadog.
• Maintain CI/CD pipelines for data infrastructure using Terraform, GitHub Actions, or similar tools.

Requirements

• 5+ years of experience in data engineering, infrastructure engineering, or a related field.
• Strong programming skills in Python, Node.js.
• Proficient in SQL and experience with distributed query engines (e.g., Trino, Presto).
• Experience with cloud-native data platforms such as AWS Glue.
• Hands-on experience with infrastructure-as-code tools (Terraform, Pulumi, CloudFormation).
• Familiarity with containerization and orchestration tools such as Kafka and Kubernetes.
• Solid understanding of data governance, quality frameworks, and data lifecycle management.
• Ability to work in a fast-paced, collaborative environment with a focus on impact and delivery.
• Experience in streaming data architecture and tools like Apache Kafka, Kinesis, or Pub/Sub.
• Background in supporting machine learning or analytics platforms.
• Exposure to data mesh, data contracts, or modern data stack concepts.
• Knowledge of DevOps principles applied to data systems.

Benefits

• Health Care Plan (Medical, Dental & Vision)
• Retirement Plan (401k, IRA)
• Life Insurance
• Unlimited Paid Time Off
• 9 paid Holidays
• Family Leave
• Work From Home
• Free Food & Snacks (Access to Industrious Co-working Membership!)
• Wellness Resources