Senior Data Engineer

Role Description

The Senior Data Engineer will play a crucial role in building out the company’s enterprise data platform to support analytics and AI. As part of the Enterprise Data team, you will be tasked with the responsibility of developing quality data collection processes, maintaining the integrity of our data foundations and enabling business leaders and data scientists across the company to have rapid access to the data they need for decision-making and innovation. The role will be responsible for the infrastructure and operations of the organization's data storage solutions, third-party integrations, data provisioning services, and overall ETL/ELT code-based solutions and tooling that process data.

• Development of complex SQL queries for data extraction, manipulation, and reporting and transformation technologies.
• Design and implement robust ETL/ELT pipelines using custom-tooling (Python/Google) and off-the-shelf tooling with focus on monitoring, supportability, and resource stewardship.
• Contribute to and leverage coding standards and best practices to ensure efficient and re-usable services and components.
• Architect, implement and deploy new data models and data processes in production.
• Build data pipelines which acquire, cleanse, transform and publish data from a wide variety of sources.
• Assemble large, complex data sets which meet functional and non-functional business requirements.
• Partner with data asset managers, architects, and development leads to ensure technical solution provides data which is fit for use and in line with architecture blueprints.
• Identify, document, design, and implement internal process improvements.
• Other duties as assigned by management.

Qualifications

• Bachelor’s degree required in Data Science, Computer Science or MIS, Mathematics, Engineering, or related field.
• 5+ years of prior experience in Data Management / ETL / ELT / Data Warehousing.
• Experience in writing Data Quality routines for cleansing of data and capturing confidence score and master data management (MDM).
• Hands-on experience with designing and implementing data pipelines and ELT/ETL processes (ex. Fivetran, DBT).
• Hands-on experience with cloud platforms (ex. GCP, AWS, Azure) and related services (ex. BigQuery, S3, Snowflake, etc.).
• Strong understanding of data modeling, data integration, and data governance principles (ex. DBT).
• Experience working in a highly regulated domain (ex. Healthcare, Banking, etc.).
• Strong knowledge of Structured Query Language (SQL) and Transact-SQL (T-SQL).
• Experience using scripting languages such as JavaScript or Python.
• Experience with agile delivery methodologies.
• Strong organizational, administrative, and analytical skills required.
• Travel may be required between 5 to 10%.

Preferred Requirements

• Master's degree in Data Science, Computer Science or MIS, Mathematics, Engineering, or related field.
• DBT Certification.
• Data Modeling experience preferred.
• Experience working with Clinical Data and Regulatory Governance in a Healthcare setting.
• Experience with healthcare data models, datasets, and source systems (e.g. EHR, claims, DICOM images, labs, etc.).
• Experience with healthcare reference data (ICD, CPT etc.).
• Experience with big data technologies (ex. Kafka, Hadoop, Spark) and containerization (ex. Docker, Kubernetes).
• Experience with FHIR and FHIR store formats and data repositories.
• Hands-on design and configuration experience with cloud services Google (related to data storage and processing).
• Data Governance Principles and enterprise frameworks (Warehousing, Data-as-a-Product, MESH, MDM).
• Knowledge of HIPAA; ability to implement systems and processes in accordance with regulations.