Worth
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 for both our employees and customers. Worth AI is seeking a Data Infrastructure Engineer to build and maintain the foundational systems that power our data platform. In this role, you will design, implement, and optimize scalable, reliable, and secure data infrastructure supporting analytics, data science, and product applications across the organization. The ideal candidate will have extensive experience with modern data architectures, cloud platforms, and data orchestration tools. You should be passionate about automation, performance tuning, and ensuring high availability of data services. This is a critical role within our data team and offers the opportunity to influence the long-term data strategy of the company. Responsibilities Design, build, and maintain scalable and resilient data infrastructure in cloud environments (AWS, Azure, 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.
Minimum Requirements
5+ years of experience in data engineering, infrastructure engineering, or a related field. Strong programming skills in Python and 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 focused 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
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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 for both our employees and customers. Worth AI is seeking a Data Infrastructure Engineer to build and maintain the foundational systems that power our data platform. In this role, you will design, implement, and optimize scalable, reliable, and secure data infrastructure supporting analytics, data science, and product applications across the organization. The ideal candidate will have extensive experience with modern data architectures, cloud platforms, and data orchestration tools. You should be passionate about automation, performance tuning, and ensuring high availability of data services. This is a critical role within our data team and offers the opportunity to influence the long-term data strategy of the company. Responsibilities Design, build, and maintain scalable and resilient data infrastructure in cloud environments (AWS, Azure, 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.
Minimum Requirements
5+ years of experience in data engineering, infrastructure engineering, or a related field. Strong programming skills in Python and 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 focused 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
#J-18808-Ljbffr