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Surescripts · 3 days ago

Senior Cloud DataOps Engineer

United States

Full-time

Remote

Senior Level

$134K/yr - $164K/yr

5+ years exp

Surescripts serves the nation through simpler, trusted health intelligence sharing, in order to increase patient safety, lower costs and ensure quality care. The Senior Cloud DataOps Engineer plays a pivotal role in designing, building, and maintaining scalable, reliable cloud infrastructure on the Google Cloud Platform to support data and analytics workflows, data products, and data pipelines.

Information TechnologyReal TimeSecuritySoftware

Growth Opportunities

No H1B

Responsibilities

Data Transformations and Data Fusion: Support Cloud components for data processing (e-g, operational data pipelines for ETL/ELT, using Python, SQL, and other relevant cloud technologies.) from various sources, by ensuring monitoring, logging, alerting and automations components are configured and available for data engineering teams

Data Cleansing, De-Identification, Data Masking: Use appropriate cloud infrastructure components and functions to support data accuracy and consistency by enabling and configuring tools and processes to protect sensitive information by removing or obfuscating personal identifiers, and securing data by replacing sensitive information with cryptographic hashes

Containerization: Leverage containers and containerization technologies such as Kubernetes, GKE, DataProc or similar cloud compute orchestration

Cloud Processing Composition: Setup and support Composer or (Apache) Airflow, or similar cloud/cluster processing task orchestration experience

Infrastructure Management: Provision, configure, and manage GCP resources using IaC (Terraform) e-g, resource provisioning, virtual machines, virtual private cloud, cloud storage. Cloud SQL, automations, monitoring, logging, security components (IAM, Firewall, Encryption) support data processing and analytics workloads and solutions

DevOps Practices: Implement and promote DevOps principles, including CI/CD pipelines, infrastructure as code (IaC), and monitoring and alerting in partnership with Network Technology and Operations Department’s System Operations function

Data Quality and Governance: Implement, configure and integrate data governance tools e-g Informatica, data quality observability tools e-g Bigeye. Google Dataplex Data Quality

Performance Optimization: Analyze and optimize data pipeline Infrastructure components, analytics application performance, identifying bottlenecks and implementing strategies to improve efficiency

Troubleshooting and Support: Diagnose and resolve infrastructure issues promptly, providing technical support to data engineers, data scientists and BI analysts

Continuous Learning: Stay abreast of industry trends, emerging technologies, and best practices in cloud data operations

Understand all applicable data privacy and security laws, rules, regulations, and contractual restrictions, and follow all Surescripts data governance and data usage rights policies and procedures

Qualification

Google Cloud PlatformDataOps practicesInfrastructure as CodeETL/ELT processesData governance toolsPythonSQLApache AirflowKubernetesData quality conceptsTroubleshooting skillsCollaboration skillsCommunication skillsContinuous learning

Required

Bachelor's degree in Computer Science, Data Science, or other related field; or equivalent experience

5+ years of progressive experience in DevOps roles, with a strong focus on GCP or other Cloud providers

3+ years of experience in healthcare transaction data, including data engineering, and reporting

Experience with DevOps practices, CI/CD pipelines, Rest API integrations and infrastructure as code (IaC using Terraform)

Strong knowledge of data warehousing/data lake, ETL/ELT processes, and reporting layers solutions

Expertise in the various cloud data, compute and storage technologies, and their appropriate use-cases. These will include Columnar (e.g., BigQuery), NoSQL (e.g., BigTable), and relational (e.g., AlloyDB)

Fluency in a relevant cloud programming language such as Python or Java / JavaScript

Proficiency with SQL, Relational, NoSQL, and Columnar databases, and Structured and Unstructured data

Familiarity with data quality and governance concepts and implementation

Proficiency with cloud processing orchestration technologies, such as Apache Airflow, DataProc, and Kubernetes (e.g., GKE)

Knowledge of privacy laws and regulations around health data (HIPAA) and PII

Ability to work independently and as part of a team with excellent collaboration and communication skills