Ntrs
Cloud Data Platform Engineer
Chicago, IL
No sponsorship$137k-$234kDetected 5 hours ago
PythonJavaScalaGitSQLSnowflakeRedshiftDatabricksAWSAzureCloud PlatformsDockerKubernetesTerraformCI/CDDevOpsPlatform EngineeringKafkaMachine LearningAirflowdbtData EngineeringComplianceAccessibility
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odds of building a lasting career here
37Unrated
Cap-exempt (no lottery)0
Sponsors this role0
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
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About the role
- This role partners with architects, product owners, and application teams to deliver modern data platform capabilities that accelerate innovation while ensuring operational excellence, governance, security, and cost efficiency.
- The engineer drives automation, platform standardization, and continuous improvement to provide reliable and self-service data services across the organization.
- The Cloud Data Platform Engineer is responsible for designing, implementing, operating, and evolving a scalable, secure, reliable and high-performance cloud-based data platform that enables data warehousing, analytics, artificial intelligence capabilities, and business-critical data platform services built on a modern Lakehouse architecture.
Responsibilities
- Design, implement, operate, and continuously improve cloud-based data platform services and infrastructure supporting enterprise data, analytics, and AI workloads on technologies including Databricks, Snowflake, Azure and AWS.
- Support self-service data platform capabilities by developing standardized onboarding, provisioning, and operational processes for platform consumers.
- Build and maintain scalable Lakehouse architecture capabilities that support structured, semi-structured, and unstructured data at enterprise scale.
- Implement CI/CD, Infrastructure as Code (IaC), and configuration management practices using enterprise-standard automation and deployment tools including Terraform and automated provisioning.
- Develop and maintain reusable Infrastructure as Code modules, deployment templates, and platform blueprints to ensure standardization and operational consistency.
- Develop platform services, automation, and documentation that enable self-service onboarding, provisioning, governance, and operational management.
- Design and maintain GitHub-based CI/CD pipelines to automate platform provisioning, application deployment, testing, and operational workflows.
- Build reusable frameworks and automation for data workflows, monitoring, and scaling.
- Develop and optimize frameworks that enable data ingestion, transformation, orchestration, processing, and AI-powered workloads across the platform ensuring a reliable and efficient data lifecycle.
Requirements
- Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future.
- Education & Experience:
- Proven expertise in building data pipelines with tools like Azure data factory, Synapse, Apache Airflow, dbt, Kafka, or similar.
- Skills & Competencies:
- Knowledge of FinOps principles for cost-efficient data platform design.
Nice to have
- Bachelor's degree in computer science, Data Engineering, or related field (Master's preferred).
- 7+ years of experience in data engineering, cloud engineering, or platform engineering.
- Hands-on experience with at least one major cloud provider (Azure, AWS).
- Strong experience with Cloud Data platform like Snowflake and Databricks.
- Proven expertise in Devops engineering including cloud infrastructure resources creation, Data object change management and other IAAC's.
- Experience operating cloud platforms within regulated environments with strong governance, audit, security, and compliance requirements preferred.
Skills
- Proficiency in infrastructure-as-code (Github, Copilot, Terraform, yaml, Azure Devops, devSecops, CloudFormation, Pulumi).
- Experience in cloud data platform like Databricks or Snowflake.
- Experience in programming languages (Sql, Python, yaml, Java, or Scala).
- Deep understanding of cloud-native data services (e.g., Azure Synapse, Data Factory, Azure App services, AWS Redshift, Glue, S3, Athena).
- Familiarity with containerization and orchestration (Docker, Kubernetes).
- Strong problem-solving, communication, and cross-functional collaboration skills.
- Uptime, performance, and reliability of the cloud data platform.
- Data availability, quality, and accessibility for business and analytics use cases.
- Efficiency and scalability of data pipelines and processing.
- Adoption and effectiveness of automation, Infrastructure as Code, and self-service platform capabilities.
- Cost optimization and resource utilization of cloud data services.
- Adoption and satisfaction of data platform services by business and analytics teams
Compensation
- $137,400 - 233,600 USD
- Salary range is a good faith estimate of base pay.
Benefits
- Northern Trust also provides a discretionary bonus program that may include an equity component.
- As a Northern Trust partner, you will be part of a flexible and collaborative work culture, which has a strong history of financial strength and stability.
- Northern Trust is committed to working with and providing adjustments to individuals with health conditions and disabilities.
Company info
- Philanthropy is deeply rooted in Northern Trust's history and is an essential element of our culture.
Equal opportunity
- Reasonable Accommodation
- If you need a reasonable accommodation for any part of the employment process, please email our HR Service Center at MyHRHelp@ntrs.com, or alternatively you can discuss your individual requirements with the recruiter you are working with.
Visa & Work Authorization
- Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future.
- Northern Trust will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa).
This listing is sourced directly from Ntrs's careers page and normalized into a canonical job model.