Sr Cloud Data Engineer

ERC Pathlight • Aspen, CO

2d • $145,000 - $175,000

About The Position

The Senior Cloud Data Engineer at ERC Pathlight is responsible for designing, building, and maintaining scalable data pipelines that enable reliable, accessible, and high-quality data across the organization. This role supports clinical, operational, and analytical teams by transforming raw data into actionable insights, helping drive informed decision-making and improved patient outcomes. By ensuring the integrity and performance of our data systems, the Senior Data Engineer plays a key role in advancing ERC Pathlight’s mission to provide evidence-based treatment for mood, anxiety, and eating disorders. This is a key role in building the Enterprise Data Warehouse (EDW) for ERC Pathlight.

Requirements

• Bachelors degree in Computer Science, Data Science, Information Systems, Software Engineering, Computer Engineering, or other applicable field.
• Over 5 years of experience in designing and implementing conceptual, logical, and physical data models in both transactional and analytical environments for healthcare organizations.
• Over 5 years of recent hands-on experience in designing and implementing cloud data engineering solutions in the healthcare domain.
• Over 8 years of experience in Deep understanding of data normalization and denormalization principles, relational database design, and performance optimization.
• Over 10 Years of experience in developing cloud data warehousing, data lake, data marts and centralized data ecosystem using various ETL tools and database management system.
• Over 8 years of experience translating complex business and clinical requirements into scalable data structures that support reporting, analytics, and interoperability.
• Over 5 years of experience in healthcare industry-standard healthcare data models (e.g., CDISC SDTM/ADaM, OMOP, FHIR, HL7).
• Over 7 years of experience in developing, automating, and optimizing scalable data pipelines using Azure Data Factory, Azure Synapse Analytics, and Azure Databricks to ingest, transform, and load data from various sources into cloud-based data lakes and warehouses.
• Over 7 years of experience in Implementing robust data models and architecture using Azure SQL Database, Azure Lake Storage Gen2, and Delta Lake to support analytics, BI, and machine learning cases.
• Over 7 years of experience in developing and maintaining ADF pipelines, data flows, and integration runtimes, ensuring reliable and scalable data ingestion into Azure Data Lake, Azure SQL, and Synapse Analytics.
• Over 5 years of experience in master data management & data quality, metadata management, data lineage, business glossaries & definition documentation, ensuring transparency and traceability of model elements.
• Over 7 years of experience in designing and developing complex Azure Data Factory (ADF) pipelines to orchestrate data ingestion, transformation, and loading (ETL/ELT) across hybrid data sources including SQL Server, REST APIs, Blob Storage, and third-party services.
• Over 3 years of experience designing and implementing AI/ML pipelines and training data models for analytics engines using a variety of cloud-based analytics tools
• Over 3 years of leading and principal data engineering experience in data integration, modeling, data quality, validation and security.
• Possess outstanding communication (written and verbal), listening and interpersonal skills; and be able to quickly establish credibility and rapport with a broad set of executives and constituencies.
• Proven track record of collaboration and relationship building across diverse teams in a heterogeneous environment.
• Ability to develop and enhance partnership with customers, take ownership of issues, and assist customers in navigating ITS using "warm handoffs" and other related techniques.
• Ability to prepare and give presentations, and to communicate (written and verbal) complex technical content to technical and non-technical stakeholders.
• Ability to work with customers to conduct detailed requirements gathering and analyze information to translate customer objectives into a detailed technical implementation plan.
• Experience mentoring, coaching and training staff, and creating personal development plans.

Responsibilities

• Lead and strongly work on enterprise cloud data engineering, design, and data management techniques and principles related to data warehousing, operations data stores, data marts, data lake design, and other emerging technologies.
• Design and orchestrate batch and real-time data ingestion workflows using Azure Data Factory (ADF) and other ETL tools such as Informatica IICS, Snowflake, AWS Glue, etc.
• Heavily works on building, testing, deploying, and monitoring scalable ETL/ELT pipelines using Azure Data Factory and related Azure services.
• Lead and work on data pipelines for troubleshooting, development of triggers, automatic failure notification, optimizing, and cost-tuning Azure-based data pipelines and cloud workflows.
• Integrate data from a wide range of cloud data systems, cloud storage and web applications, such as Meta Ads, Google Ads, GA4, BigQuery, Salesforce, and REST APIs using Azure Data Factory.
• Querying, managing, and optimizing datasets within Azure SQL Database and Azure Synapse Analytics.
• Work with Azure Data Lake and Azure Blob Storage to manage structured and unstructured data assets.
• Develop robust pipelines to ingest data from databases, sFTP, file-based systems, and external APIs within the Azure ecosystem.
• Strongly work on Azure data and AI ecosystem, with proficiency in services such as Azure Data Lake, Azure Synapse Analytics, Azure ML, Azure SQL Database, and seamless integration of ADF pipelines with AI/ML workflows.
• Develop and operationalize AI/ML pipelines, including preparing training datasets, orchestrating model training/inference, and integrating ML models into data workflows using ADF, Azure ML, Databricks, or Synapse ML.
• Lead and implement and uphold coding standards, manage code reviews, and lead data validation and testing (unit, integration, and regression) and other documentations.
• Lead and establish ETL coding standards, EDW naming conventions, and other best practices for EDW development.
• Store healthcare data vocabulary, business glossaries, data dictionaries such as SNOMED CT, LOINC, ICD-10, and RxNorm etc. inside EDW.
• Lead, implement and adopt Azure board, CI/CD pipelines, including branching strategies, version control (e.g., Git), and automated deployments.
• Guide and mentor data engineering team on ETL development, troubleshoot, document creation, Proof of concept projects and other data engineering initiatives.
• Lead data modeling initiatives including data normalization, denormalization, relational database design, and using data modeling tools such as ER/Studio, Erwin, or SQL Power Architect.
• Adopt and EDW clinical data model, including conceptual, logical, and physical model design for both transactional and analytical systems.
• Design and implement scalable, cloud-optimized data models (e.g., star, snowflake, or data vault) to support analytical and operational workloads.
• Optimize data models for performance, cost-efficiency, and maintainability across cloud data warehouses like BigQuery, Redshift, Synapse, Azure SQL, or Snowflake.
• Develop and maintain data quality frameworks, including data profiling, validation, and cleansing strategies.
• Lead and drive metadata management and data lineage practices that support auditability, compliance, and governance.
• Design and implement secure data pipelines on cloud platforms, ensuring encryption at rest and in transit also build various quality frames such an encryption, tokenization, patterning etc.
• Collaborate with security teams to enforce IAM policies, audit logs, and compliance with standards like HIPAA, GDPR, or SOC 2.
• Monitor and remediate vulnerabilities in data infrastructure, leveraging tools for threat detection and incident response.
• Implement data cataloging and lineage tools such as Purview, Informatica EDC, Collabra etc. to support discoverability, traceability, and compliance requirements.
• Build data validation frameworks such as Audit, Balance and Control (ABC) frameworks to ensure accuracy, completeness, and consistency across pipelines.
• Lead and manage end-of-the-end data engineering projects by tracking deliverables and timelines using tools like Smartsheet and Excel, ensuring realistic scheduling and on-time delivery of all project milestones and task line items.
• Lead the exploration and establishment of an agentic AI/ML and clinical advanced analytics framework, contributing to proof-of-concept (POC) initiatives and study models to support future development.
• Diagnosis and resolving bottlenecks in large-scale data pipelines such as Azure Data Factory, Data Lake, Databricks, snowflake etc. applying root cause analysis and creative solutions to ensure system reliability and efficiency.
• Pioneer scalable data pipeline architectures such as Hub and Spoke, Medallion architecture, SOA, Datamart’s/data Warehouse etc. using emerging cloud technologies, driving automation and cost optimization across data platforms.
• Partner closely with data scientists, analysts, and cross-functional teams to gather requirements, design data models, and deliver high-impact solutions aligned with business goals including offshore and global data engineering and analytics team.
• Create high-level design documents, mapping specification documents, and detailed design documents, and present them in various forums such as analytics roundtables, working groups, monthly showcases, and other stakeholder meetings.
• Strongly collaborate with business, clinical, and technical stakeholders to align data initiatives with organizational goals and regulatory requirements (e.g., HIPAA, GDPR).
• Lead, advocate and manage project timelines, prioritize tasks, adapt to changing requirements, and deliver high-quality data solutions on time.

Benefits

• We offer competitive compensation; comprehensive medical, dental, and vision coverage; generous Paid Time Off; Parental Leave benefits; Retirement benefits; and tuition reimbursement to help you continue growing in your career.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level