As a Principal Architect, you are a leader and visionary in your field, collaborating with and leading the work of cross-functional teams including: technical program management, product management, structural engineering, civil engineering, mechanical engineering, electrical engineering, supply chain management, operations, safety, security, finance, and legal.

Technical Skills: Proficiency in statistical programming languages (R, Python, Julia), SQL, and data engineering tools (dbt, Spark, Snowflake, BigQuery, LookerStudio). Data Engineering: Leverage data engineering tools such as dbt, Spark, and Snowflake to manage and process large datasets effectively.

Will serve as a trusted counsel for the Head of HR Data Engineering, CDO (Chief Data Officer) and Engineering Managers. Data engineering tools (Airflow, Beam, Spark.

5 years software solution development using agile, DevOps, operating in a product model that includes designing, developing, and implementing large-scale applications or data engineering solutions.

The Asset Management Quant Research Engineering team is looking for a Director of Data Engineering who wishes to take on the challenge of building a world-class data operation.

In-depth and applied knowledge of data engineering tools and techniques, including ML Ops, Databricks and/or Snowflake, AWS, DBT, AI/GenAI Data Pipelines, Data Automation, Python, Model Monitoring, and Alerting.

8+ years of experience in batch and streaming ETL using Spark, Python, Java, Snowflake or Databricks for Data Engineering or Machine Learning workloads. Establish clear communication channels and ensure understanding between engineering teams, architecture, data science, and product.

Required: Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, or related field.

Manage budget, resources, and tools necessary for data engineering projects. Job Summary : We are seeking an experienced Leader for our Data Engineering team. Stay current with emerging trends and technologies in data engineering and recommend innovative solutions to enhance our capabilities and drive business value.

Expertise in data integration, ETL tools, and data engineering programming/scripting languages (Python, Scala, SQL) for data preparation and analysis. The Principal Data Engineer role will work closely with cross-functional product teams and 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 (structured and unstructured data.

Data Engineering & Analytics Lead Are you a skilled, experienced Data Engineering & Analytics professional seeking a leadership position in the healthcare industry? If you are passionate about leveraging data to drive meaningful insights and have a proven track record in data engineering, analytics, and leadership we invite you to join us on this exciting journey.

Statistics, operations research, bioinformatics, economics, computational biology, computer science, mathematics, physics, electrical engineering, industrial engineering). We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.

The Data Architect will be held accountable for the following responsibilities: Define and implement the long-term technology strategy and innovations roadmaps across analytics, data engineering, and data platformsCreate standards, design patterns, and best practices for ETL development in an enterprise data warehouse environment.

10 years of experience in data engineering, data architecture, BI & Analytics, and/or Data Science. Modern Data Stack experience (Snowflake, Synpase, Databricks, Redshift, DBT, and/or Airflow.

Minimum of 5 years of hands-on skills in Python, Apache Spark, Hive, Cassandra, Snowflake, Elastic, Lucene, DataBricks, Hadoop, Redshift, Scala, Java, or other relevant technologies in data engineering.