Data Engineer

Role Overview

• Build and optimize analytical data models in BigQuery.
• Implement partitioning, clustering, and materialized views for performance and cost efficiency.
• Ensure compliance with data governance, access controls, and IAM best practices.
• Develop integrations with external systems (APIs, flat files etc.) using GCP-native or hybrid approaches.
• Utilize tools like Dataflow or custom Python/Java services on Cloud Functions or Cloud Run to handle transformations and ingestion logic.
• Build automated CI/CD pipeline using Cloud Build, GitHub Actions, or Jenkins for deploying data pipeline code and workflows.
• Set up observability using Cloud Monitoring, Cloud Logging, and Error Reporting to ensure pipeline reliability.
• Collaborate with teams to craft tools to provide actionable insights and integrate them with consumer touchpoints.

Requirements

• 1+ years of experience with SQL, NoSQL
• 1+ years of experience with Python (or a comparable scripting language)
• 1+ years of experience with Data warehouses (such as data modeling and technical architectures) and infrastructure components
• 1+ years of experience with ETL/ELT, and building high-volume data pipelines
• 1+ years of experience with reporting/analytic tools
• 1+ years of experience with query optimization, data structures, transformation, metadata, dependency, and workload management
• 1+ years of experience with Big data and cloud architecture
• 1+ years of hands-on experience building modern data pipelines within a major cloud platform (GCP)
• 1+ years of experience with deployment/scaling of apps on containerized environment (i.e. Kubernetes, AKS)
• 1+ years of experience with real-time and streaming technology (i.e. Kafka, Spark Streaming)
• Experience with complex systems and solving challenging analytical problems
• Strong collaboration and communication skills within and across teams
• Knowledge of data visualization and reporting
• Experience in designing and building data engineering solutions in cloud environments (preferably GCP)
• Experience with Git, CI/CD pipeline, and other DevOps principles/best practices
• Experience with bash shell scripts, UNIX utilities & UNIX Commands
• Understanding of software development methodologies including waterfall and agile
• Ability to leverage multiple tools and programming languages to analyze and manipulate data sets from disparate data sources
• Knowledge of API development
• Experience with schema design and dimensional data modeling
• Google Professional Data Engineer Certification
• Knowledge of microservices and SOA
• Formal SAFe and/or agile experience.
• Previous healthcare experience and domain knowledge
• Experience designing, building, and maintaining data processing systems
• Experience architecting and building data warehouse and data lakes

Tech Stack

• BigQuery
• Cloud
• ETL
• Google Cloud Platform
• Java
• Jenkins
• Kafka
• Kubernetes
• Microservices
• NoSQL
• Python
• Spark
• SQL
• Unix

Benefits

• medical coverage
• dental coverage
• vision coverage
• paid time off
• retirement savings options
• wellness programs
• additional resources, based on eligibility