Senior Data Architect

1 month ago

Chicago, Illinois, United States Gateway Recruiting, INC. Full time
Job Overview

Gateway Recruiting, INC. is seeking a highly skilled Principal Machine Learning Engineer to join our team. The successful candidate will be responsible for designing, developing, and deploying state-of-the-art data engineering techniques and streamlined data ingestion processes to extract valuable insights and intelligence from large and complex medical datasets.

Key Responsibilities:

  • Lead and contribute hands-on to major data engineering initiatives from inception to delivery.
  • Analyze data to identify trends and insights.
  • Collaborate with product and engineering teams to define data requirements and drive data-driven decision making.
  • Design and implement data models to effectively support various product use cases.
  • Design, implement, and maintain scalable and optimized data architectures that meet evolving business needs.
  • Evaluate and recommend appropriate data storage solutions, ensuring data accessibility and integrity.
  • Develop and continuously optimize data ingestion processes for improved reliability and performance.
  • Design, build, and maintain robust data pipelines and platforms.
  • Establish monitoring and alerting systems to proactively identify and address potential data pipeline issues.
  • Support Data infrastructure needs such as cluster management and permission.
  • Develop and maintain internal tools to streamline data access and analysis for all teams.
  • Create and deliver documentation to educate product teams on data best practices and tools.
  • Communicate technical concepts effectively to both technical and non-technical audiences.

Requirements:

  • Master's Degree in Data Science, Computer Science, Statistics, or a related field plus 10 years of experience in data engineering with a strong focus on data architecture and data ingestion.
  • Experience in the Life Science Industry.
  • Strong understanding of data modeling (conceptual, logical, and physical) using different data modeling methodologies and analytics concepts.
  • Proven experience designing, building, and maintaining data pipelines and platforms.
  • Expertise working with data integration and ETL tools, and data engineering programming/scripting languages (Python, Scala, SQL) for data preparation and analysis.
  • Experience with Data Ops (VPCs, cluster management, permissions, Databricks configurations, Terraform) in Cloud Computing environments (e.g., AWS, Azure, GCP) and associated cloud data platforms, cloud data warehouse technologies (Snowflake/Redshift), and Advanced Analytical platforms (e.g., Dataiku and Databricks).
  • Familiarity with data streaming technologies like Kafka and Debezium.
  • Proven expertise with data visualization tools (e.g., Tableau, Power BI).
  • Strong understanding of data security principles and best practices.
  • Experience with CI/CD pipelines and automation tools.
  • Strong problem-solving and critical thinking skills.
  • Excellent written and verbal communication skills to convey complex technical concepts and findings to non-technical stakeholders and collaborate effectively across teams.

Preferred:

  • Prior experience with healthcare domain data, including Electronic Health Records (EHR).
  • Experience with triple stores or graph databases (e.g., GraphDB, Stardog, Jena Fuseki)
  • Proficient with building domain ontologies and relevant W3C standards - RDF, RDFS, OWL, SKOS, SPARQL and associated Ontology Editors (e.g., TopBraid Composer, Protégé).
  • Experience with semantic validation languages (e.g. SHACL, SPIN) and associated semantic software packages and frameworks (e.g., Jena, Sesame, RDF4J, RDFLib).
  • Knowledge of data governance and compliance policies.

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